Conversation
…tion - Add AttractAttempt interface for tracking attract outcomes - Implement closed-loop learning: createAttempt, recordReply, recordActionsTriggered, finalizeAttempt - Score attempts based on actions triggered (human=10, conversion=+10, agent=3, reply=1, negative=-5) - Show attempt history to LLM for in-context pattern matching - Add comprehensive JSDoc comments with WHY explanations throughout - Rewrite README with architecture, learning system, and configuration docs
WalkthroughThis PR implements a comprehensive learning and reactive trigger system for arcade-style attract mode. Key additions include: reactive trigger modes with configurable delays, in-memory attempt tracking with 30-minute outcome windows, sentiment-based reply analysis, action tracking with conversion detection, attempt history persistence, and score-based learning mechanics. The system now differentiates human and agent interactions and adapts future attract prompts based on outcomes. Changes
Sequence DiagramssequenceDiagram
participant Client
participant AttractService
participant AttractAction
participant LLM
participant Memory
participant AttractSentinel
Client->>AttractService: checkRooms() / processReactiveQueue()
AttractService->>AttractService: Finalize expired attempts
AttractService->>AttractAction: Invoke with room context
AttractAction->>AttractService: createAttempt(roomId, trigger msg)
AttractService->>Memory: Store attempt in-memory
AttractAction->>LLM: Generate attract message
LLM->>AttractAction: Return message or "..."
alt LLM Opt-Out
AttractAction->>AttractService: Schedule 30-min retry
else Normal Flow
AttractAction->>Client: Send via callback (attract msg)
AttractAction->>Memory: recordAttracts (message)
AttractAction->>AttractService: createAttempt tracking
end
Client->>AttractSentinel: handleReply / actionTriggered
AttractSentinel->>AttractService: recordReply(isHuman, sentiment)
AttractSentinel->>AttractService: recordActionsTriggered(isHuman, actions)
loop Within 30-minute window
AttractSentinel->>AttractService: Track engagement
end
AttractService->>AttractService: finalizeAttempt() at window end
AttractService->>AttractService: calculateScore(attempt)
AttractService->>Memory: Persist to attract_history DB
sequenceDiagram
participant Room
participant AttractService
participant ReactiveQueue
participant Evaluator
Room->>AttractService: READY state detected + MESSAGE_RECEIVED
AttractService->>AttractService: Check conditions (pending attempts, budget, queue status)
alt Conditions Met
AttractService->>ReactiveQueue: Queue room with configurable delay
Note over AttractService: reactiveDelayMs (default or config)
else Conditions Failed
Note over AttractService: Skip reactive queue
end
Note over ReactiveQueue: 5-second check loop
ReactiveQueue->>AttractService: processReactiveQueue()
AttractService->>AttractService: getReactiveAttractRooms()
AttractService->>Evaluator: Process up to 3 rooms
Evaluator->>Evaluator: Run attract action + sentinel
Evaluator->>AttractService: Remove room from queue post-send
Note over AttractService: Ready for next reactive cycle
Estimated code review effort🎯 4 (Complex) | ⏱️ ~50 minutes
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src/services/attract.ts
Outdated
| // Also persist to DB | ||
| try { | ||
| await this.runtime.createMemory({ | ||
| id, | ||
| entityId: this.runtime.agentId, | ||
| roomId, | ||
| content: { | ||
| text: message, | ||
| type: 'attract_attempt', | ||
| source: 'attract_service', | ||
| attempt: JSON.stringify(attempt), | ||
| }, | ||
| createdAt: now, | ||
| }, 'attract_history'); |
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logic: duplicate memory creation: the same attempt is persisted in both createAttempt (here) and finalizeAttempt (line 1151) with the same ID. This will cause the second write to overwrite the first.
Consider only persisting once in finalizeAttempt, or use different IDs/update logic.
Prompt To Fix With AI
This is a comment left during a code review.
Path: src/services/attract.ts
Line: 1000:1013
Comment:
**logic:** duplicate memory creation: the same attempt is persisted in both `createAttempt` (here) and `finalizeAttempt` (line 1151) with the same ID. This will cause the second write to overwrite the first.
Consider only persisting once in `finalizeAttempt`, or use different IDs/update logic.
How can I resolve this? If you propose a fix, please make it concise.| if (attempt.actionsTriggeredByHuman.length > 0) { | ||
| score += 10; | ||
| } |
There was a problem hiding this comment.
style: score of 10 is awarded if ANY human action exists, regardless of how many. 5 actions = 10pts, 1 action = 10pts. Consider scaling with action count for more granular scoring.
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: src/services/attract.ts
Line: 1198:1200
Comment:
**style:** score of 10 is awarded if ANY human action exists, regardless of how many. 5 actions = 10pts, 1 action = 10pts. Consider scaling with action count for more granular scoring.
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
src/providers/attract.ts
Outdated
| outcome = `→ ${a.score}pts (${a.actionsTriggeredByHuman.join(', ')} triggered)`; | ||
| } else if (a.humanReplies > 0) { | ||
| outcome = `→ ${a.score}pt (${a.humanReplies} replies)`; |
There was a problem hiding this comment.
style: outcome string only shows actions if actionsTriggeredByHuman exists, but ignores actionsTriggeredByAgent. Multi-agent coordination signals might be lost in the history display.
Prompt To Fix With AI
This is a comment left during a code review.
Path: src/providers/attract.ts
Line: 37:39
Comment:
**style:** outcome string only shows actions if `actionsTriggeredByHuman` exists, but ignores `actionsTriggeredByAgent`. Multi-agent coordination signals might be lost in the history display.
How can I resolve this? If you propose a fix, please make it concise.There was a problem hiding this comment.
Pull request overview
This PR adds a comprehensive learning system to the attract plugin, enabling LLMs to "learn" from past attract attempts by showing them historical outcomes in subsequent prompts. The implementation tracks attract attempt outcomes (replies, actions triggered, sentiment) and scores them to help the LLM pattern-match successful approaches.
Key Changes:
- Implemented closed-loop learning system with attempt tracking (create, record, finalize)
- Added scoring algorithm based on action triggers and engagement (human actions=10pts, conversions=+10pts, agent actions=3pts, replies=1pt, negative=-5pts)
- Enhanced documentation with extensive "WHY" explanations throughout the codebase
Reviewed changes
Copilot reviewed 8 out of 8 changed files in this pull request and generated 6 comments.
Show a summary per file
| File | Description |
|---|---|
| src/types.ts | Added AttractAttempt interface with comprehensive outcome tracking fields and extensive documentation |
| src/templates/attract.ts | Updated template to include attempt history and learning context for the LLM |
| src/services/attract.ts | Implemented learning system methods (createAttempt, recordReply, recordActionsTriggered, finalizeAttempt, calculateScore) |
| src/providers/attract.ts | Added formatAttemptHistory function and integrated attempt history into template context |
| src/index.ts | Added architecture overview documentation explaining the learning system flow |
| src/evaluators/attractSentinel.ts | Enhanced to track replies, sentiment, and actions triggered during the response window |
| src/actions/attract.ts | Integrated attempt creation and finalization into the attract flow |
| README.md | Expanded with learning system documentation, scoring rationale, and troubleshooting guidance |
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| await this.runtime.createMemory({ | ||
| id: attempt.id, | ||
| entityId: this.runtime.agentId, | ||
| roomId, | ||
| content: { | ||
| text: attempt.message, | ||
| type: 'attract_attempt', | ||
| source: 'attract_service', | ||
| attempt: JSON.stringify(attempt), | ||
| }, | ||
| createdAt: attempt.sentAt, | ||
| }, 'attract_history'); |
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Using the same ID for both create and finalize operations could cause issues. When finalizeAttempt is called, it calls createMemory with the same attempt.id, which may conflict with the initial creation in createAttempt. This could lead to duplicate entries or update failures depending on how the memory system handles ID conflicts. Consider using an update operation if available, or ensuring the memory system can handle overwrites properly.
| if (a.actionsTriggeredByHuman.length > 0) { | ||
| outcome = `→ ${a.score}pts (${a.actionsTriggeredByHuman.join(', ')} triggered)`; | ||
| } else if (a.humanReplies > 0) { | ||
| outcome = `→ ${a.score}pt (${a.humanReplies} replies)`; | ||
| } else { | ||
| outcome = `→ 0pts (silence)`; |
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The score display formatting is inconsistent. When there are human replies without actions, it shows "1pt" (singular), but when showing actions triggered or silence, it shows "pts" (plural). For consistency and clarity, all scores should use the same format, either always "pt" or always "pts", or use conditional formatting based on the score value.
src/evaluators/attractSentinel.ts
Outdated
| if (pendingAttempt) { | ||
| // Record this reply | ||
| // WHY: Count human vs agent replies separately. Human engagement is the goal. | ||
| await attractService.recordReply(message.roomId, isHuman, sentiment); | ||
|
|
||
| // Check if this message triggered any actions (from the agent's response) | ||
| // WHY: Actions are the real success metric. Someone saying "play jazz" triggers | ||
| // PLAY_AUDIO - that's what we want, not just "nice message". | ||
| if (responses && responses.length > 0) { | ||
| const agentResponse = responses[0]; | ||
| const actionsTriggered = agentResponse.content?.actions || []; | ||
|
|
||
| if (actionsTriggered.length > 0) { | ||
| // Filter out non-actionable actions like IGNORE, NONE | ||
| // WHY: REPLY and IGNORE are default behaviors, not real capability usage | ||
| const meaningfulActions = actionsTriggered.filter( | ||
| (a: string) => !['IGNORE', 'NONE', 'REPLY'].includes(a) | ||
| ); | ||
|
|
||
| if (meaningfulActions.length > 0) { | ||
| // Record which actions were triggered and by whom | ||
| // WHY: Human triggering PLAY_AUDIO (10pts) > agent triggering it (3pts) | ||
| await attractService.recordActionsTriggered( | ||
| message.roomId, | ||
| isHuman, | ||
| meaningfulActions | ||
| ); | ||
| } | ||
| } | ||
| } | ||
| } | ||
|
|
||
| // ============================================ | ||
| // STRIKE SYSTEM (Existing) | ||
| // ============================================ | ||
|
|
||
| // Check if there was a recent attract message (within last 5 minutes) | ||
| const timeSinceLastAttract = Date.now() - tracking.lastAttractAt; | ||
| const recentAttract = timeSinceLastAttract < 5 * 60 * 1000; // 5 minutes |
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The evaluator tracks replies for all pending attempts within their response window, but it only applies strikes for negative feedback within a 5-minute window of the attract. This creates an inconsistency: positive tracking happens for 30 minutes, but negative tracking only happens for 5 minutes. This could skew the learning data, as negative responses that arrive between 5-30 minutes won't be recorded as negative sentiment in the attempt, but won't trigger strikes either. Consider aligning these windows or documenting this intentional asymmetry more clearly.
| // Create a new attempt to track outcomes (learning system) | ||
| // WHY: Start the 30-minute tracking window. The evaluator will record replies | ||
| // and actions, and we'll finalize with a score before the next attract. | ||
| await attractService.createAttempt(message.roomId, attractText); |
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The attempt is created after recording the attract message. If createAttempt throws an error or fails to persist to the database (even though it's caught), the attract message will be sent without any attempt tracking. This means the learning system won't capture any data for that attract. Consider creating the attempt before sending the message, or at minimum ensuring that a failed attempt creation doesn't silently continue, potentially by using the returned attempt ID in subsequent operations.
src/services/attract.ts
Outdated
| // Human replied but no action (mild signal) | ||
| if (attempt.humanReplies > 0 && attempt.actionsTriggeredByHuman.length === 0) { |
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The scoring logic has a potential edge case: if a human triggers both actions AND replies, but there are multiple human triggered actions, the score would be 10 (for actions) but not include the reply bonus of 1 point. However, if a human triggers actions AND has a conversion, the score could be 20+ points, which seems correct. But the condition on line 1213 (attempt.humanReplies > 0 && attempt.actionsTriggeredByHuman.length === 0) means that human replies are only valued when NO actions were triggered. This seems intentional based on the scoring rationale, but it means a human who both replies AND triggers an action gets the same score (10 points) as one who just triggers an action silently. Consider if this is the desired behavior or if reply engagement should add incremental value even when actions are triggered.
| // Human replied but no action (mild signal) | |
| if (attempt.humanReplies > 0 && attempt.actionsTriggeredByHuman.length === 0) { | |
| // Human replied (engagement signal) | |
| if (attempt.humanReplies > 0) { |
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Actionable comments posted: 3
🧹 Nitpick comments (2)
src/index.ts (1)
258-276: Consider adding method signatures to AttractService interface.The event handlers use
(attractService as any)type casts to callhandleMessageReceivedandhandleWorldConnected. If these are intended public methods, they should be properly typed.This would improve type safety and IDE support:
// In AttractService or a separate interface public handleMessageReceived(payload: MessagePayload): Promise<void>; public handleWorldConnected(payload: any): Promise<void>;src/services/attract.ts (1)
1023-1032: Expired attempts returned as null may become orphaned.When
getPendingAttemptreturns null for an expired attempt (line 1030), the attempt remains inpendingAttemptswithout finalization. WhilefinalizeExpiredAttemptshandles this incheckRooms, there's a window where queries may see stale data.Consider proactively finalizing when detecting an expired attempt:
public getPendingAttempt(roomId: UUID): AttractAttempt | null { const attempt = this.pendingAttempts.get(roomId); if (!attempt) return null; if (attempt.finalized) return null; - if (Date.now() > attempt.windowEndsAt) return null; // Expired + if (Date.now() > attempt.windowEndsAt) { + // Don't block, but schedule finalization + this.finalizeAttempt(roomId).catch(() => {}); + return null; + } return attempt; }
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📒 Files selected for processing (8)
README.mdsrc/actions/attract.tssrc/evaluators/attractSentinel.tssrc/index.tssrc/providers/attract.tssrc/services/attract.tssrc/templates/attract.tssrc/types.ts
🧰 Additional context used
🧬 Code graph analysis (2)
src/providers/attract.ts (1)
src/types.ts (2)
AttractAttempt(210-272)AttractSettings(41-119)
src/services/attract.ts (1)
src/types.ts (1)
AttractAttempt(210-272)
🪛 LanguageTool
README.md
[grammar] ~71-~71: Use a hyphen to join words.
Context: ...|---------|--------|-----------| | Human triggered action | 10 | Primary goal - s...
(QB_NEW_EN_HYPHEN)
[grammar] ~73-~73: Use a hyphen to join words.
Context: ...fined high value (sales, tips) | | Agent triggered action | 3 | Multi-agent coord...
(QB_NEW_EN_HYPHEN)
🪛 markdownlint-cli2 (0.18.1)
README.md
84-84: Fenced code blocks should have a language specified
(MD040, fenced-code-language)
211-211: Fenced code blocks should have a language specified
(MD040, fenced-code-language)
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- GitHub Check: Greptile Review
🔇 Additional comments (19)
src/templates/attract.ts (2)
1-29: Well-documented philosophy section.The "WHY" explanations for the template design choices (intent over structure, in-context learning, escape hatch) provide valuable context for future maintainers.
30-65: Template structure looks correct and aligns with provider.The new conditional blocks (
attractHistory,coldStart,recentAttracts,attractExamples) are well-integrated. The techniques section provides useful guidance without being prescriptive.src/actions/attract.ts (4)
122-125: Good learning loop integration.Finalizing the previous attempt before generating a new one ensures the tracking window closes properly and scores are calculated.
127-135: Multi-agent jitter implementation looks reasonable.The 0-30s random delay combined with the vibe check provides good collision prevention. Consider logging even when jitter is ≤1000ms for debugging purposes, though this is minor.
176-193: LLM opt-out handling is well-implemented.The "..." escape hatch respects both character authenticity and community by scheduling a retry instead of forcing output. The 30-minute retry delay is reasonable.
208-211: Attempt creation starts the learning window.This correctly starts tracking outcomes for the new attract message immediately after sending.
src/providers/attract.ts (1)
63-70: Good history and cold start logic.The coldStart threshold of 3 attempts is reasonable for determining when the LLM has enough history for pattern matching.
src/evaluators/attractSentinel.ts (3)
213-235: Action recording from agent responses.The logic correctly filters out non-actionable actions (IGNORE, NONE, REPLY) and records meaningful actions. The assumption that
responses[0]is the agent's response should be documented.
241-280: Strike and engagement tracking is well-structured.The separation of the 5-minute strike window from the 30-minute attempt tracking window is a good design choice with clear rationale.
154-162: Inline comment already addresses platform-specific concern.The code at line 162 already includes a comment (line 161) acknowledging that the
fromBotmetadata check is platform-specific and suggesting future improvements. The suggestion to add documentation is already present in the form of:// For now, assume non-bot entityIds are human (platform-specific detection could be added). No further action needed.Likely an incorrect or invalid review comment.
README.md (1)
55-90: Comprehensive learning system documentation.The scoring rationale table and template output examples clearly explain how the learning system works. This will help operators understand and tune their agents.
src/types.ts (2)
210-272: Well-designed AttractAttempt interface.The interface captures all necessary data for the learning system with clear documentation. The separation of human vs agent tracking and the conversion flag provide flexible scoring.
121-168: RoomAttractMetadata supports the FSM well.The in-memory tracking fields are appropriate for the state machine, with clear WHY documentation for each field.
src/index.ts (2)
121-136: Good retry pattern for service availability.The 5-second retry loop for service availability handles the startup race condition gracefully.
174-201: Message sending callback is well-structured.The callback properly routes through AttractService, creates memory records, and handles failures gracefully.
src/services/attract.ts (4)
1078-1098: Sentiment tracking logic is correct.The "most negative wins" approach ensures that any negative feedback during the window is properly captured for scoring.
1194-1223: Scoring implementation matches documented rationale.The point values (10 for human action, +10 conversion bonus, 3 for agent action, 1 for reply, -5 for negative) align with the README documentation.
922-948: Clear documentation for the learning system architecture.The comments explain the rationale for in-memory pending vs DB finalized attempts, which helps future maintainers understand the design.
1149-1162: VerifycreateMemorybehavior with duplicate IDs in @elizaos/core.
finalizeAttemptcallscreateMemorywith the same ID generated increateAttempt. The comment "Update in DB" and code structure suggest this should upsert the existing record, but the actual behavior depends on the@elizaos/coreimplementation, which is not accessible in this repository. Confirm whethercreateMemorytreats IDs as unique keys for upsert operations or creates duplicate entries.
| function formatAttemptHistory(attempts: AttractAttempt[]): string { | ||
| if (attempts.length === 0) return ''; | ||
|
|
||
| return attempts.map(a => { | ||
| const msgPreview = a.message.length > 40 | ||
| ? a.message.substring(0, 40) + '...' | ||
| : a.message; | ||
|
|
||
| let outcome = ''; | ||
| if (a.actionsTriggeredByHuman.length > 0) { | ||
| outcome = `→ ${a.score}pts (${a.actionsTriggeredByHuman.join(', ')} triggered)`; | ||
| } else if (a.humanReplies > 0) { | ||
| outcome = `→ ${a.score}pt (${a.humanReplies} replies)`; | ||
| } else { | ||
| outcome = `→ 0pts (silence)`; | ||
| } | ||
|
|
||
| return `- "${msgPreview}" ${outcome}`; | ||
| }).join('\n'); | ||
| } |
There was a problem hiding this comment.
Minor: Inconsistent point labeling (singular vs plural).
Line 37 uses ${a.score}pts while line 39 uses ${a.score}pt. This inconsistency could confuse the LLM's pattern matching.
🔎 Proposed fix
if (a.actionsTriggeredByHuman.length > 0) {
outcome = `→ ${a.score}pts (${a.actionsTriggeredByHuman.join(', ')} triggered)`;
} else if (a.humanReplies > 0) {
- outcome = `→ ${a.score}pt (${a.humanReplies} replies)`;
+ outcome = `→ ${a.score}pts (${a.humanReplies} replies)`;
} else {
outcome = `→ 0pts (silence)`;
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| function formatAttemptHistory(attempts: AttractAttempt[]): string { | |
| if (attempts.length === 0) return ''; | |
| return attempts.map(a => { | |
| const msgPreview = a.message.length > 40 | |
| ? a.message.substring(0, 40) + '...' | |
| : a.message; | |
| let outcome = ''; | |
| if (a.actionsTriggeredByHuman.length > 0) { | |
| outcome = `→ ${a.score}pts (${a.actionsTriggeredByHuman.join(', ')} triggered)`; | |
| } else if (a.humanReplies > 0) { | |
| outcome = `→ ${a.score}pt (${a.humanReplies} replies)`; | |
| } else { | |
| outcome = `→ 0pts (silence)`; | |
| } | |
| return `- "${msgPreview}" ${outcome}`; | |
| }).join('\n'); | |
| } | |
| function formatAttemptHistory(attempts: AttractAttempt[]): string { | |
| if (attempts.length === 0) return ''; | |
| return attempts.map(a => { | |
| const msgPreview = a.message.length > 40 | |
| ? a.message.substring(0, 40) + '...' | |
| : a.message; | |
| let outcome = ''; | |
| if (a.actionsTriggeredByHuman.length > 0) { | |
| outcome = `→ ${a.score}pts (${a.actionsTriggeredByHuman.join(', ')} triggered)`; | |
| } else if (a.humanReplies > 0) { | |
| outcome = `→ ${a.score}pts (${a.humanReplies} replies)`; | |
| } else { | |
| outcome = `→ 0pts (silence)`; | |
| } | |
| return `- "${msgPreview}" ${outcome}`; | |
| }).join('\n'); | |
| } |
🤖 Prompt for AI Agents
In src/providers/attract.ts around lines 27 to 46, the point label is
inconsistently pluralized ("pt" vs "pts"), which can confuse downstream pattern
matching; change the string construction to choose "pt" when a.score === 1 and
"pts" otherwise (use a small conditional or helper like const pointLabel =
a.score === 1 ? 'pt' : 'pts') and use `${a.score}${pointLabel}` in all three
outcome branches (including the zero score case) so the wording is consistent
across the map.
![cursor[bot]](https://avatars.githubusercontent.com/in/1210556?s=60&v=4){kind=small}
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
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Actionable comments posted: 1
♻️ Duplicate comments (1)
src/evaluators/attractSentinel.ts (1)
107-109: Learning system tracking blocked by 5-minute validation window.The validator rejects messages after 5 minutes, but the learning system is designed to track outcomes for
responseWindowMs(default 30 minutes). SincerecordReplyandrecordActionsTriggeredare only called from this evaluator's handler, replies/actions between 5-30 minutes are never recorded. The JSDoc comment on line 32 claims this is "handled elsewhere" but no such mechanism exists.Consider either:
- Extending the validation window to match
responseWindowMs- Adding a separate mechanism to track replies during the full response window
🧹 Nitpick comments (1)
src/evaluators/attractSentinel.ts (1)
160-162: Consider defensive handling forfromBotmetadata.If
message.metadata?.fromBotis undefined (common case),isHumandefaults totrue. This is likely intentional, but consider adding a more explicit check or logging when the metadata is missing to help debug unexpected behavior in production.
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Cache: Disabled due to data retention organization setting
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📒 Files selected for processing (1)
src/evaluators/attractSentinel.ts
🧰 Additional context used
🪛 Biome (2.1.2)
src/evaluators/attractSentinel.ts
[error] 241-241: Expected a catch clause but instead found 'const'.
Expected a catch clause here.
(parse)
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🔇 Additional comments (2)
src/evaluators/attractSentinel.ts (2)
11-39: Clear documentation explaining the design rationale.The WHY explanations for the timing windows and tracking strategy are valuable for future maintainers.
266-279: Positive engagement tracking looks good.The engagement signal with
isHumanflag and timestamp provides useful data for the learning system.
- Add force parameter to finalizeAttempt() - defaults to false - Only finalize if window expired (unless force=true) - Action uses force=true when starting new attract (attribution clarity) - Prevents cutting short data collection if window still open Fixes premature finalization issue from PR review
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Actionable comments posted: 1
♻️ Duplicate comments (5)
src/actions/attract.ts (2)
122-128: Force finalization addresses previous concern.The addition of
force=trueparameter properly addresses the premature finalization issue flagged in previous reviews. The WHY comment clearly explains the attribution trade-off: partial data is preferable to corrupted data when starting a new attract.
211-214: Attempt creation after message send risks data loss.Creating the attempt after sending the message (line 209) means if
createAttemptfails or throws, the attract message is delivered but no tracking exists. The learning system loses all data for that attract. While the error is caught (line 241), the silent failure breaks the feedback loop.🔎 Suggested approach: Create attempt before sending
- // Record to memory for anti-repetition (persisted to DB) - // WHY: LLMs have no memory between calls. Without this, they'd repeat the same - // "killer" message over and over. By showing recent messages in the prompt, - // we get variety. - await attractService.recordAttract(message.roomId, attractText); - // Create a new attempt to track outcomes (learning system) // WHY: Start the 30-minute tracking window. The evaluator will record replies // and actions, and we'll finalize with a score before the next attract. await attractService.createAttempt(message.roomId, attractText); + // Record to memory for anti-repetition (persisted to DB) + // WHY: LLMs have no memory between calls. Without this, they'd repeat the same + // "killer" message over and over. By showing recent messages in the prompt, + // we get variety. + await attractService.recordAttract(message.roomId, attractText); + // Log telemetryThis ensures the attempt exists before the message is sent, preventing silent tracking failures.
src/services/attract.ts (3)
1154-1192: Force parameter implementation looks correct.The force parameter properly addresses the premature finalization concern from previous reviews. Line 1161 respects the window unless forced, and the WHY comment explains the attribution trade-off.
However, this still suffers from the duplicate ID persistence issue (see comment on lines 1000-1021).
1215-1244: Consider scaling score with action count for better granularity.Currently, any human action triggers a flat 10-point bonus (line 1219-1221). This means 1 action = 10pts and 5 actions = 10pts, losing signal about engagement depth. While the binary approach is simpler, scaling could provide more nuanced learning data.
🔎 Optional: Scale score with action count
// Human triggered actions (the main goal) if (attempt.actionsTriggeredByHuman.length > 0) { - score += 10; + score += Math.min(10 + (attempt.actionsTriggeredByHuman.length - 1) * 2, 20); + // 1 action = 10pts, 2 actions = 12pts, 3+ actions = 14-20pts (capped) }Alternatively, keep the current flat scoring if simplicity is preferred—it's easier for the LLM to interpret.
1000-1021: Critical: Duplicate persistence with same ID breaks learning system.Both
createAttempt(lines 1002-1013) andfinalizeAttempt(lines 1172-1183) callcreateMemorywith the sameattempt.id. Standard database semantics cause the second call to fail when the ID already exists, or silently overwrite the initial record. The comment at line 1170 says "Update in DB" but uses create semantics.Impact: When finalization fails (caught silently at line 1187), the database retains the original record with
finalized: false,score: 0, and empty action arrays. SincegetAttemptHistory(line 1051) filters to only finalized attempts, no historical data ever appears in the learning prompt—completely breaking the learning system.🔎 Proposed fix: Only persist finalized attempts, or use update semantics
Option 1 (Recommended): Only persist when finalized
// Store in memory for fast access this.pendingAttempts.set(roomId, attempt); - // Also persist to DB - try { - await this.runtime.createMemory({ - id, - entityId: this.runtime.agentId, - roomId, - content: { - text: message, - type: 'attract_attempt', - source: 'attract_service', - attempt: JSON.stringify(attempt), - }, - createdAt: now, - }, 'attract_history'); - - logger.debug(`[Attract] Created attempt ${id} for room ${roomId}`); - } catch (error) { - logger.error({ error }, '[Attract] Failed to persist attempt to DB'); - } + logger.debug(`[Attract] Created attempt ${id} for room ${roomId} (in-memory, will persist when finalized)`); return id;Option 2: Check if runtime supports update/upsert operations
#!/bin/bash # Search for update or upsert memory operations in @elizaos/core rg -nP '\b(updateMemory|upsertMemory)\s*\(' --type=ts -C3If an update method exists, use it in
finalizeAttemptinstead ofcreateMemory.
📜 Review details
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Review profile: CHILL
Plan: Pro
Cache: Disabled due to data retention organization setting
Knowledge base: Disabled due to data retention organization setting
📒 Files selected for processing (2)
src/actions/attract.tssrc/services/attract.ts
🧰 Additional context used
🧬 Code graph analysis (1)
src/services/attract.ts (1)
src/types.ts (1)
AttractAttempt(210-272)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
- GitHub Check: Cursor Bugbot
🔇 Additional comments (4)
src/services/attract.ts (4)
394-395: LGTM: Expired attempt finalization integrated into check loop.Calling
finalizeExpiredAttempts()before processing room states ensures learning data is persisted at regular intervals. This prevents data loss if the service restarts before manual finalization.
922-948: LGTM: Clear documentation of learning system philosophy.The WHY comments effectively explain the "memory not learning" approach and justify the in-memory + DB hybrid architecture. This helps future maintainers understand the design decisions.
1026-1065: LGTM: Pending attempt and history retrieval logic is sound.The expiry check on line 1030 prevents stale attempts from being returned, and the finalized filter on line 1051 ensures only complete data enters the learning prompt.
1233-1236: Scoring logic intentionally excludes replies when actions exist.Line 1234's condition
attempt.actionsTriggeredByHuman.length === 0means human replies only add +1 point when NO actions were triggered. A human who both replies AND triggers an action gets 10 points (same as one who triggers an action silently). This appears intentional based on the scoring philosophy (actions > replies), but worth confirming this behavior aligns with your goals.Is it intentional that human replies add zero incremental value when actions are triggered? If engagement (reply + action) should be valued higher than silent usage (action only), consider adjusting the condition.
- Remove duplicate persistence in createAttempt (only persist when finalized) - Fix evaluator: restore if(responses) check, use agentResponse.content - Prevents duplicate ID errors that broke learning system
- Check callback exists before any state changes - Only record attract/create attempt AFTER message is sent - Prevents consuming budget/cooldown for unsent messages - Returns failure if no callback provided
- Change action extraction from agent response to user message content - Remove duplicate memory creation by only persisting in finalizeAttempt - Add expiration check before finalizing previous attempts to respect 30-minute tracking window - Scale engagement score based on action count instead of binary check - Include agent-triggered actions in outcome string for visibility - Move attempt creation before sending attract message for atomicity - Standardize score display to always use plural "pts" format - Align strike window with response tracking window for consistency
- Change action extraction from agent response to user message content - Remove duplicate memory creation by only persisting in finalizeAttempt - Add expiration check before finalizing previous attempts to respect 30-minute tracking window - Scale engagement score based on action count instead of flat 10pts - Include agent-triggered actions in outcome string for visibility - Use consistent plural "pts" formatting in score display - Move attempt creation before recording attract message to ensure tracking exists if message sends successfully - Document tracking window inconsistency between replies and strikes
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Actionable comments posted: 5
🤖 Fix all issues with AI agents
In @.pr-resolver-state.json:
- Around line 842-870: Remove the exposed tokens from the
.pr-resolver-state.json artifact by redacting or replacing the sensitive
JWT/API-key-like strings found in the "commentBody" field (e.g., entries
referencing long base64-like tokens), then remove the generated resolver-state
artifact from commits and add the artifact pattern to .gitignore to prevent
re-committing; if the credentials were actually used, rotate/revoke those keys
immediately and perform a git history rewrite (git filter-repo/BFG) to purge the
leaked secrets from the repo history.
In `@CLAUDE.md`:
- Around line 8-12: The CLAUDE.md file uses bold text
"**src/evaluators/attractSentinel.ts**" as a section label which markdownlint
flags; replace that bold-as-heading with a proper Markdown heading (e.g., "###
src/evaluators/attractSentinel.ts") so the file section uses a real heading,
improves TOC rendering and fixes the lint warning; update any other file section
labels in CLAUDE.md that use bold the same way to consistent heading syntax.
In `@src/actions/attract.ts`:
- Around line 122-129: Pending attempts can be overwritten by createAttempt;
before calling attractService.createAttempt ensure any pending attempt for
message.roomId is handled: use attractService.getPendingAttempt(message.roomId)
and if it exists and its windowEndsAt is in the future either call
attractService.finalizeAttempt(message.roomId) (force finalize) or abort/skip
the new attract (return early); if you choose finalize, await finalizeAttempt
and handle errors (log/throw) before proceeding to attractService.createAttempt
to avoid data loss.
In `@src/evaluators/attractSentinel.ts`:
- Around line 166-194: The current logic in the sentiment detection (variables
messageText, negativeKeywords, matchedKeyword, sentiment) allows a positive
reaction (hasPositiveReaction) to overwrite a previously detected negative
keyword; change the reaction-handling block so that negative reactions always
set sentiment = 'negative' and positive reactions set sentiment = 'positive'
only if sentiment is not already 'negative' (i.e., do not overwrite an existing
negative sentiment from keywords or reactions), preserving matchedKeyword when
negative.
In `@src/services/attract.ts`:
- Around line 953-964: getResponseWindowMs() and getConversionActions() read
fields that are never populated because getSettings() doesn't merge the
env/character config into the returned settings; update getSettings() so it
pulls/merges responseWindowMs and conversionActions from the source config
(e.g., character config or environment overrides) into the settings object
before returning. In practice, locate getSettings() and ensure it copies/merges
(responseWindowMs, conversionActions) from the canonical config (e.g.,
this.character.config or process.env) so getResponseWindowMs(),
getConversionActions() see the configured values.
| { | ||
| "commentId": "PRRC_kwDOQlMfNs6eNcBK", | ||
| "reason": "Lines 208-215 now check for callback existence before proceeding, and lines 217-221 send the message before lines 227-232 record state and create attempt.", | ||
| "dismissedAt": "2026-01-26T22:22:38.350Z", | ||
| "dismissedAtIteration": 0, | ||
| "category": "already-fixed", | ||
| "filePath": "src/actions/attract.ts", | ||
| "line": 232, | ||
| "commentBody": "The attempt is created after recording the attract message. If `createAttempt` throws an error or fails to persist to the database (even though it's caught), the attract message will be sent without any attempt tracking. This means the learning system won't capture any data for that attract. Consider creating the attempt before sending the message, or at minimum ensuring that a failed attempt creation doesn't silently continue, potentially by using the returned attempt ID in subsequent operations." | ||
| }, | ||
| { | ||
| "commentId": "PRRC_kwDOQlMfNs6eNegE", | ||
| "reason": "The current code at lines 230-235 shows properly balanced braces. The structure is: `if (responses...)` -> `if (actionsTriggered.length > 0)` -> `if (meaningfulActions.length > 0)` with proper closing braces at 231-234 matching the three nested blocks plus the outer `if (pendingAttempt)` block.", | ||
| "dismissedAt": "2026-01-26T22:22:38.350Z", | ||
| "dismissedAtIteration": 0, | ||
| "category": "already-fixed", | ||
| "filePath": "src/evaluators/attractSentinel.ts", | ||
| "line": 235, | ||
| "commentBody": "_⚠️ Potential issue_ | _🔴 Critical_\n\n**Critical: Syntax error from extra closing brace.**\n\nThere are 4 closing braces (lines 231-234) but only 3 opening braces (lines 205, 216, 223). The extra `}` at line 233 prematurely closes the `try` block, causing the static analysis error at line 241 (\"Expected a catch clause but instead found 'const'\").\n\nAdditionally, `agentResponse` on line 213 is defined but never used.\n\n<details>\n<summary>🔎 Proposed fix</summary>\n\n```diff\n if (pendingAttempt) {\n // Record this reply\n // WHY: Count human vs agent replies separately. Human engagement is the goal.\n await attractService.recordReply(message.roomId, isHuman, sentiment);\n\n // Check if this message triggered any actions (from the agent's response)\n // WHY: Actions are the real success metric. Someone saying \"play jazz\" triggers\n // PLAY_AUDIO - that's what we want, not just \"nice message\".\n- const agentResponse = responses[0];\n- const actionsTriggered = message.content?.actions || [];\n+ const actionsTriggered = message.content?.actions || [];\n\n- if (actionsTriggered.length > 0) {\n- // Filter out non-actionable actions like IGNORE, NONE\n- // WHY: REPLY and IGNORE are default behaviors, not real capability usage\n- const meaningfulActions = actionsTriggered.filter(\n- (a: string) => !['IGNORE', 'NONE', 'REPLY'].includes(a)\n- );\n+ if (actionsTriggered.length > 0) {\n+ // Filter out non-actionable actions like IGNORE, NONE\n+ // WHY: REPLY and IGNORE are default behaviors, not real capability usage\n+ const meaningfulActions = actionsTriggered.filter(\n+ (a: string) => !['IGNORE', 'NONE', 'REPLY'].includes(a)\n+ );\n\n- if (meaningfulActions.length > 0) {\n- // Record which actions were triggered and by whom\n- // WHY: Human triggering PLAY_AUDIO (10pts) > agent triggering it (3pts)\n- await attractService.recordActionsTriggered(\n- message.roomId,\n- isHuman,\n- meaningfulActions\n- );\n- }\n+ if (meaningfulActions.length > 0) {\n+ // Record which actions were triggered and by whom\n+ // WHY: Human triggering PLAY_AUDIO (10pts) > agent triggering it (3pts)\n+ await attractService.recordActionsTriggered(\n+ message.roomId,\n+ isHuman,\n+ meaningfulActions\n+ );\n }\n }\n- }\n+ }\n```\n</details>\n\n<details>\n<summary>🤖 Prompt for AI Agents</summary>\n\n```\nIn src/evaluators/attractSentinel.ts around lines 205 to 234, there is an extra\nclosing brace that prematurely closes the try block and causes a syntax error;\nremove the stray `}` (the extra closing brace at ~line 233) so the braces\nbalance and the subsequent catch/const block stays inside the correct scope, and\nalso either delete the unused variable `agentResponse` declared at ~line 213 or\nuse it where intended (e.g., reference responses[0] where needed) to avoid the\nunused-variable lint error.\n```\n\n</details>\n\n<!-- fingerprinting:phantom:medusa:ocelot -->\n\n<!-- This is an auto-generated comment by CodeRabbit -->\n\n✅ Addressed in commit bc7c6ca" | ||
| }, | ||
| { | ||
| "commentId": "PRRC_kwDOQlMfNs6eOVFp", | ||
| "reason": "Lines 208-215 now check `if (!callback)` and return early with `success: false` BEFORE any state recording. Lines 217-221 send via callback, and only THEN do lines 227-232 call `recordAttract` and `createAttempt`.", | ||
| "dismissedAt": "2026-01-26T22:22:38.350Z", | ||
| "dismissedAtIteration": 0, | ||
| "category": "already-fixed", | ||
| "filePath": "src/actions/attract.ts", | ||
| "line": 233, | ||
| "commentBody": "### Attract records state and returns success without sending\n\n<!-- **Medium Severity** -->\n\n<!-- DESCRIPTION START -->\nThe action calls `recordAttract` and `createAttempt` (persisting to DB, updating `lastAttractAt`, incrementing `dailyBudget`, creating a learning attempt) BEFORE checking if `callback` exists to actually send the message. If `callback` is undefined, all state is recorded as if the attract was sent, but no message is delivered. The function still returns `success: true`. This consumes daily budget, sets cooldown, and creates misleading learning data for messages users never received.\n<!-- DESCRIPTION END -->\n\n<!-- LOCATIONS START\nsrc/actions/attract.ts#L208-L239\nLOCATIONS END -->\n<a href=\"https://cursor.com/open?data=eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCIsImtpZCI6ImJ1Z2JvdC12MiJ9.eyJ2ZXJzaW9uIjoxLCJ0eXBlIjoiQlVHQk9UX0ZJWF9JTl9DVVJTT1IiLCJkYXRhIjp7InJlZGlzS2V5IjoiYnVnYm90OjY2NTZkYjVlLTBjNDEtNDU2MC1hNTUxLTYyYTg4Zjg0ZGVkNSIsImVuY3J5cHRpb25LZXkiOiJ0TGtZTkxxSU0xSjlmNUZnTkhKTEVqclVoQ0lmZzJJX1FPNzM1dFY2Rl8wIiwiYnJhbmNoIjoib2RpLWRldiJ9LCJpYXQiOjE3NjcxNDUwMDQsImV4cCI6MTc2OTczNzAwNH0.oi39sxph8vqODoKoRB7hWbpszryTx1XniJqVA9IxdOmEpJA4eUl_272V9ctPFm0HZXOmfoDufEwXwlH3bj8T7P44fUuxbUoqndLNtxp206W3CuL8lxrzvCcjqTUF3N5lS8Ys52XJ8SV9bVm56qeLSqDBbBo3Riv0GQbqh6mpsQE3PlwtmfarKAvG1JgU0cuxzMK6OkDfaGU8lL26rkmHgc6StBg_T6yzzVpGzoInSBfp6AnxiIkBtsqxvRGKwVqI4sTiB7NODroPt78VVW60PSQf0zCxVbwbqM_hzuyQRHU9swo8PUG9YYViB6yXYkknpmMkHbROVBu3aS9yaXFgBw\" target=\"_blank\" rel=\"noopener noreferrer\"><picture><source media=\"(prefers-color-scheme: dark)\" srcset=\"https://cursor.com/fix-in-cursor-dark.svg\"><source media=\"(prefers-color-scheme: light)\" srcset=\"https://cursor.com/fix-in-cursor-light.svg\"><img alt=\"Fix in Cursor\" src=\"https://cursor.com/fix-in-cursor.svg\"></picture></a> <a href=\"https://cursor.com/agents?data=eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCIsImtpZCI6ImJ1Z2JvdC12MiJ9.eyJ2ZXJzaW9uIjoxLCJ0eXBlIjoiQlVHQk9UX0ZJWF9JTl9XRUIiLCJkYXRhIjp7InJlZGlzS2V5IjoiYnVnYm90OjY2NTZkYjVlLTBjNDEtNDU2MC1hNTUxLTYyYTg4Zjg0ZGVkNSIsImVuY3J5cHRpb25LZXkiOiJ0TGtZTkxxSU0xSjlmNUZnTkhKTEVqclVoQ0lmZzJJX1FPNzM1dFY2Rl8wIiwiYnJhbmNoIjoib2RpLWRldiIsInJlcG9Pd25lciI6ImVsaXphb3MtcGx1Z2lucyIsInJlcG9OYW1lIjoicGx1Z2luLWF0dHJhY3QiLCJwck51bWJlciI6MSwiY29tbWl0U2hhIjoiYmM3YzZjYTAwNzg2NmRiY2FhMTBkMzA4ZjVlZjQ1NzkyNDI0MzkwNyIsInByb3ZpZGVyIjoiZ2l0aHViIn0sImlhdCI6MTc2NzE0NTAwNCwiZXhwIjoxNzY5NzM3MDA0fQ.Zop7t3hiEPSAMFSntuCD0ZWB0MxxiTGxsi4ICnKFiYSVfvDGcjdno6oIkTBSei6EFjcBbXIYJ7mkbdHZUkaqHRUVtW5WgDISOUJmLLPGFVerVEHX4KK8FfgKHPDY0RZXmip7ooR45LSP0ys7D-MkirTxh81zWaYtAzPeMX8WsXnMtoHOrNa9bsFQenMHawujbVAULkbvXIMz6ePg8dB0HruELjJUpuXrYjcdpIgTnCAXJphCTWjsFmlLUMLbNz-SQQvkYj45SqSE5YU99F8PFFiwT4utB6lWxJUbrLBjiCFtXOAlk_gNhborP82400q-2n-6oiim5q5q0OB_H4YeQg\" target=\"_blank\" rel=\"noopener noreferrer\"><picture><source media=\"(prefers-color-scheme: dark)\" srcset=\"https://cursor.com/fix-in-web-dark.svg\"><source media=\"(prefers-color-scheme: light)\" srcset=\"https://cursor.com/fix-in-web-light.svg\"><img alt=\"Fix in Web\" src=\"https://cursor.com/fix-in-web.svg\"></picture></a>\n\n" |
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Redact embedded credentials from resolver-state artifact.
The commentBody includes JWT/API-key-like tokens (gitleaks flagged). Committing these is a security risk; redact the payload or drop this artifact from the repo (and gitignore it if generated).
🧹 Proposed redaction
- "commentBody": "### Attract records state and returns success without sending
- ... (embedded links/tokens) ..."
+ "commentBody": "[REDACTED: removed embedded tokens/links from resolver-state artifact]"📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| { | |
| "commentId": "PRRC_kwDOQlMfNs6eNcBK", | |
| "reason": "Lines 208-215 now check for callback existence before proceeding, and lines 217-221 send the message before lines 227-232 record state and create attempt.", | |
| "dismissedAt": "2026-01-26T22:22:38.350Z", | |
| "dismissedAtIteration": 0, | |
| "category": "already-fixed", | |
| "filePath": "src/actions/attract.ts", | |
| "line": 232, | |
| "commentBody": "The attempt is created after recording the attract message. If `createAttempt` throws an error or fails to persist to the database (even though it's caught), the attract message will be sent without any attempt tracking. This means the learning system won't capture any data for that attract. Consider creating the attempt before sending the message, or at minimum ensuring that a failed attempt creation doesn't silently continue, potentially by using the returned attempt ID in subsequent operations." | |
| }, | |
| { | |
| "commentId": "PRRC_kwDOQlMfNs6eNegE", | |
| "reason": "The current code at lines 230-235 shows properly balanced braces. The structure is: `if (responses...)` -> `if (actionsTriggered.length > 0)` -> `if (meaningfulActions.length > 0)` with proper closing braces at 231-234 matching the three nested blocks plus the outer `if (pendingAttempt)` block.", | |
| "dismissedAt": "2026-01-26T22:22:38.350Z", | |
| "dismissedAtIteration": 0, | |
| "category": "already-fixed", | |
| "filePath": "src/evaluators/attractSentinel.ts", | |
| "line": 235, | |
| "commentBody": "_⚠️ Potential issue_ | _🔴 Critical_\n\n**Critical: Syntax error from extra closing brace.**\n\nThere are 4 closing braces (lines 231-234) but only 3 opening braces (lines 205, 216, 223). The extra `}` at line 233 prematurely closes the `try` block, causing the static analysis error at line 241 (\"Expected a catch clause but instead found 'const'\").\n\nAdditionally, `agentResponse` on line 213 is defined but never used.\n\n<details>\n<summary>🔎 Proposed fix</summary>\n\n```diff\n if (pendingAttempt) {\n // Record this reply\n // WHY: Count human vs agent replies separately. Human engagement is the goal.\n await attractService.recordReply(message.roomId, isHuman, sentiment);\n\n // Check if this message triggered any actions (from the agent's response)\n // WHY: Actions are the real success metric. Someone saying \"play jazz\" triggers\n // PLAY_AUDIO - that's what we want, not just \"nice message\".\n- const agentResponse = responses[0];\n- const actionsTriggered = message.content?.actions || [];\n+ const actionsTriggered = message.content?.actions || [];\n\n- if (actionsTriggered.length > 0) {\n- // Filter out non-actionable actions like IGNORE, NONE\n- // WHY: REPLY and IGNORE are default behaviors, not real capability usage\n- const meaningfulActions = actionsTriggered.filter(\n- (a: string) => !['IGNORE', 'NONE', 'REPLY'].includes(a)\n- );\n+ if (actionsTriggered.length > 0) {\n+ // Filter out non-actionable actions like IGNORE, NONE\n+ // WHY: REPLY and IGNORE are default behaviors, not real capability usage\n+ const meaningfulActions = actionsTriggered.filter(\n+ (a: string) => !['IGNORE', 'NONE', 'REPLY'].includes(a)\n+ );\n\n- if (meaningfulActions.length > 0) {\n- // Record which actions were triggered and by whom\n- // WHY: Human triggering PLAY_AUDIO (10pts) > agent triggering it (3pts)\n- await attractService.recordActionsTriggered(\n- message.roomId,\n- isHuman,\n- meaningfulActions\n- );\n- }\n+ if (meaningfulActions.length > 0) {\n+ // Record which actions were triggered and by whom\n+ // WHY: Human triggering PLAY_AUDIO (10pts) > agent triggering it (3pts)\n+ await attractService.recordActionsTriggered(\n+ message.roomId,\n+ isHuman,\n+ meaningfulActions\n+ );\n }\n }\n- }\n+ }\n```\n</details>\n\n<details>\n<summary>🤖 Prompt for AI Agents</summary>\n\n```\nIn src/evaluators/attractSentinel.ts around lines 205 to 234, there is an extra\nclosing brace that prematurely closes the try block and causes a syntax error;\nremove the stray `}` (the extra closing brace at ~line 233) so the braces\nbalance and the subsequent catch/const block stays inside the correct scope, and\nalso either delete the unused variable `agentResponse` declared at ~line 213 or\nuse it where intended (e.g., reference responses[0] where needed) to avoid the\nunused-variable lint error.\n```\n\n</details>\n\n<!-- fingerprinting:phantom:medusa:ocelot -->\n\n<!-- This is an auto-generated comment by CodeRabbit -->\n\n✅ Addressed in commit bc7c6ca" | |
| }, | |
| { | |
| "commentId": "PRRC_kwDOQlMfNs6eOVFp", | |
| "reason": "Lines 208-215 now check `if (!callback)` and return early with `success: false` BEFORE any state recording. Lines 217-221 send via callback, and only THEN do lines 227-232 call `recordAttract` and `createAttempt`.", | |
| "dismissedAt": "2026-01-26T22:22:38.350Z", | |
| "dismissedAtIteration": 0, | |
| "category": "already-fixed", | |
| "filePath": "src/actions/attract.ts", | |
| "line": 233, | |
| "commentBody": "### Attract records state and returns success without sending\n\n<!-- **Medium Severity** -->\n\n<!-- DESCRIPTION START -->\nThe action calls `recordAttract` and `createAttempt` (persisting to DB, updating `lastAttractAt`, incrementing `dailyBudget`, creating a learning attempt) BEFORE checking if `callback` exists to actually send the message. If `callback` is undefined, all state is recorded as if the attract was sent, but no message is delivered. The function still returns `success: true`. This consumes daily budget, sets cooldown, and creates misleading learning data for messages users never received.\n<!-- DESCRIPTION END -->\n\n<!-- LOCATIONS START\nsrc/actions/attract.ts#L208-L239\nLOCATIONS END -->\n<a href=\"https://cursor.com/open?data=eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCIsImtpZCI6ImJ1Z2JvdC12MiJ9.eyJ2ZXJzaW9uIjoxLCJ0eXBlIjoiQlVHQk9UX0ZJWF9JTl9DVVJTT1IiLCJkYXRhIjp7InJlZGlzS2V5IjoiYnVnYm90OjY2NTZkYjVlLTBjNDEtNDU2MC1hNTUxLTYyYTg4Zjg0ZGVkNSIsImVuY3J5cHRpb25LZXkiOiJ0TGtZTkxxSU0xSjlmNUZnTkhKTEVqclVoQ0lmZzJJX1FPNzM1dFY2Rl8wIiwiYnJhbmNoIjoib2RpLWRldiJ9LCJpYXQiOjE3NjcxNDUwMDQsImV4cCI6MTc2OTczNzAwNH0.oi39sxph8vqODoKoRB7hWbpszryTx1XniJqVA9IxdOmEpJA4eUl_272V9ctPFm0HZXOmfoDufEwXwlH3bj8T7P44fUuxbUoqndLNtxp206W3CuL8lxrzvCcjqTUF3N5lS8Ys52XJ8SV9bVm56qeLSqDBbBo3Riv0GQbqh6mpsQE3PlwtmfarKAvG1JgU0cuxzMK6OkDfaGU8lL26rkmHgc6StBg_T6yzzVpGzoInSBfp6AnxiIkBtsqxvRGKwVqI4sTiB7NODroPt78VVW60PSQf0zCxVbwbqM_hzuyQRHU9swo8PUG9YYViB6yXYkknpmMkHbROVBu3aS9yaXFgBw\" target=\"_blank\" rel=\"noopener noreferrer\"><picture><source media=\"(prefers-color-scheme: dark)\" srcset=\"https://cursor.com/fix-in-cursor-dark.svg\"><source media=\"(prefers-color-scheme: light)\" srcset=\"https://cursor.com/fix-in-cursor-light.svg\"><img alt=\"Fix in Cursor\" src=\"https://cursor.com/fix-in-cursor.svg\"></picture></a> <a href=\"https://cursor.com/agents?data=eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCIsImtpZCI6ImJ1Z2JvdC12MiJ9.eyJ2ZXJzaW9uIjoxLCJ0eXBlIjoiQlVHQk9UX0ZJWF9JTl9XRUIiLCJkYXRhIjp7InJlZGlzS2V5IjoiYnVnYm90OjY2NTZkYjVlLTBjNDEtNDU2MC1hNTUxLTYyYTg4Zjg0ZGVkNSIsImVuY3J5cHRpb25LZXkiOiJ0TGtZTkxxSU0xSjlmNUZnTkhKTEVqclVoQ0lmZzJJX1FPNzM1dFY2Rl8wIiwiYnJhbmNoIjoib2RpLWRldiIsInJlcG9Pd25lciI6ImVsaXphb3MtcGx1Z2lucyIsInJlcG9OYW1lIjoicGx1Z2luLWF0dHJhY3QiLCJwck51bWJlciI6MSwiY29tbWl0U2hhIjoiYmM3YzZjYTAwNzg2NmRiY2FhMTBkMzA4ZjVlZjQ1NzkyNDI0MzkwNyIsInByb3ZpZGVyIjoiZ2l0aHViIn0sImlhdCI6MTc2NzE0NTAwNCwiZXhwIjoxNzY5NzM3MDA0fQ.Zop7t3hiEPSAMFSntuCD0ZWB0MxxiTGxsi4ICnKFiYSVfvDGcjdno6oIkTBSei6EFjcBbXIYJ7mkbdHZUkaqHRUVtW5WgDISOUJmLLPGFVerVEHX4KK8FfgKHPDY0RZXmip7ooR45LSP0ys7D-MkirTxh81zWaYtAzPeMX8WsXnMtoHOrNa9bsFQenMHawujbVAULkbvXIMz6ePg8dB0HruELjJUpuXrYjcdpIgTnCAXJphCTWjsFmlLUMLbNz-SQQvkYj45SqSE5YU99F8PFFiwT4utB6lWxJUbrLBjiCFtXOAlk_gNhborP82400q-2n-6oiim5q5q0OB_H4YeQg\" target=\"_blank\" rel=\"noopener noreferrer\"><picture><source media=\"(prefers-color-scheme: dark)\" srcset=\"https://cursor.com/fix-in-web-dark.svg\"><source media=\"(prefers-color-scheme: light)\" srcset=\"https://cursor.com/fix-in-web-light.svg\"><img alt=\"Fix in Web\" src=\"https://cursor.com/fix-in-web.svg\"></picture></a>\n\n" | |
| { | |
| "commentId": "PRRC_kwDOQlMfNs6eNcBK", | |
| "reason": "Lines 208-215 now check for callback existence before proceeding, and lines 217-221 send the message before lines 227-232 record state and create attempt.", | |
| "dismissedAt": "2026-01-26T22:22:38.350Z", | |
| "dismissedAtIteration": 0, | |
| "category": "already-fixed", | |
| "filePath": "src/actions/attract.ts", | |
| "line": 232, | |
| "commentBody": "The attempt is created after recording the attract message. If `createAttempt` throws an error or fails to persist to the database (even though it's caught), the attract message will be sent without any attempt tracking. This means the learning system won't capture any data for that attract. Consider creating the attempt before sending the message, or at minimum ensuring that a failed attempt creation doesn't silently continue, potentially by using the returned attempt ID in subsequent operations." | |
| }, | |
| { | |
| "commentId": "PRRC_kwDOQlMfNs6eNegE", | |
| "reason": "The current code at lines 230-235 shows properly balanced braces. The structure is: `if (responses...)` -> `if (actionsTriggered.length > 0)` -> `if (meaningfulActions.length > 0)` with proper closing braces at 231-234 matching the three nested blocks plus the outer `if (pendingAttempt)` block.", | |
| "dismissedAt": "2026-01-26T22:22:38.350Z", | |
| "dismissedAtIteration": 0, | |
| "category": "already-fixed", | |
| "filePath": "src/evaluators/attractSentinel.ts", | |
| "line": 235, | |
| "commentBody": "_⚠️ Potential issue_ | _🔴 Critical_\n\n**Critical: Syntax error from extra closing brace.**\n\nThere are 4 closing braces (lines 231-234) but only 3 opening braces (lines 205, 216, 223). The extra `}` at line 233 prematurely closes the `try` block, causing the static analysis error at line 241 (\"Expected a catch clause but instead found 'const'\").\n\nAdditionally, `agentResponse` on line 213 is defined but never used.\n\n<details>\n<summary>🔎 Proposed fix</summary>\n\n |
🧰 Tools
🪛 Gitleaks (8.30.0)
[high] 870-870: Uncovered a JSON Web Token, which may lead to unauthorized access to web applications and sensitive user data.
(jwt)
[high] 870-870: Uncovered a JSON Web Token, which may lead to unauthorized access to web applications and sensitive user data.
(jwt)
[high] 870-870: Detected a Generic API Key, potentially exposing access to various services and sensitive operations.
(generic-api-key)
[high] 870-870: Detected a Generic API Key, potentially exposing access to various services and sensitive operations.
(generic-api-key)
🤖 Prompt for AI Agents
In @.pr-resolver-state.json around lines 842 - 870, Remove the exposed tokens
from the .pr-resolver-state.json artifact by redacting or replacing the
sensitive JWT/API-key-like strings found in the "commentBody" field (e.g.,
entries referencing long base64-like tokens), then remove the generated
resolver-state artifact from commits and add the artifact pattern to .gitignore
to prevent re-committing; if the credentials were actually used, rotate/revoke
those keys immediately and perform a git history rewrite (git filter-repo/BFG)
to purge the leaked secrets from the repo history.
| ### By File | ||
|
|
||
| **src/evaluators/attractSentinel.ts** | ||
| - Fix for src/evaluators/attractSentinel.ts:215 rejected: The diff shows changes to the validate function timing window (5min to 30min), but does not address the review comment about extracting actions from `message.content?.actions` instead of from the agent's response. The suggested code change for lines 213-215 is not present in this diff. | ||
| - Fix for src/evaluators/attractSentinel.ts:null rejected: The fix changes the source to `message.content?.actions` but the review comment states the intent is to get actions "from the agent's response" - the fix goes in the opposite direction, making the unused `agentResponse` variable even more problematic and contradicting the comment's stated intent. |
There was a problem hiding this comment.
Use a heading instead of bold for the file section label.
Markdownlint flags bold-as-heading here; a real heading improves structure and TOC rendering.
♻️ Proposed fix
-**src/evaluators/attractSentinel.ts**
+### src/evaluators/attractSentinel.ts🧰 Tools
🪛 LanguageTool
[grammar] ~11-~11: Ensure spelling is correct
Context: ...to the validate function timing window (5min to 30min), but does not address the rev...
(QB_NEW_EN_ORTHOGRAPHY_ERROR_IDS_1)
[style] ~11-~11: Try using a synonym here to strengthen your wording.
Context: ...30min), but does not address the review comment about extracting actions from `message....
(COMMENT_REMARK)
🪛 markdownlint-cli2 (0.18.1)
10-10: Emphasis used instead of a heading
(MD036, no-emphasis-as-heading)
🤖 Prompt for AI Agents
In `@CLAUDE.md` around lines 8 - 12, The CLAUDE.md file uses bold text
"**src/evaluators/attractSentinel.ts**" as a section label which markdownlint
flags; replace that bold-as-heading with a proper Markdown heading (e.g., "###
src/evaluators/attractSentinel.ts") so the file section uses a real heading,
improves TOC rendering and fixes the lint warning; update any other file section
labels in CLAUDE.md that use bold the same way to consistent heading syntax.
| // Finalize any pending attempt from previous attract, but only if its window has ended. | ||
| // WHY: We need to close the learning loop once the previous attract's response window | ||
| // is actually done; otherwise, we may prematurely stop tracking late responses. | ||
| // The cooldown (24h) should normally prevent overlapping windows (24h >> 30min). | ||
| const currentAttempt = attractService.getPendingAttempt(message.roomId); | ||
| if (currentAttempt && currentAttempt.windowEndsAt <= Date.now()) { | ||
| await attractService.finalizeAttempt(message.roomId); | ||
| } |
There was a problem hiding this comment.
Finalize pending attempts before starting a new attract to avoid data loss.
createAttempt overwrites the pending attempt for a room. If a new attract fires before the prior window ends (e.g., low cooldown or manual trigger), the previous attempt is dropped without being finalized. Consider forcing finalization (or skipping the new attract) when a pending attempt exists.
🧯 Proposed fix
- if (currentAttempt && currentAttempt.windowEndsAt <= Date.now()) {
- await attractService.finalizeAttempt(message.roomId);
- }
+ if (currentAttempt) {
+ // Force-close the prior attempt to avoid overwriting and attribution drift.
+ await attractService.finalizeAttempt(message.roomId, true);
+ }🤖 Prompt for AI Agents
In `@src/actions/attract.ts` around lines 122 - 129, Pending attempts can be
overwritten by createAttempt; before calling attractService.createAttempt ensure
any pending attempt for message.roomId is handled: use
attractService.getPendingAttempt(message.roomId) and if it exists and its
windowEndsAt is in the future either call
attractService.finalizeAttempt(message.roomId) (force finalize) or abort/skip
the new attract (return early); if you choose finalize, await finalizeAttempt
and handle errors (log/throw) before proceeding to attractService.createAttempt
to avoid data loss.
| // Check message content for negative keywords | ||
| const messageText = message.content?.text?.toLowerCase() || ''; | ||
| let sentiment: 'positive' | 'neutral' | 'negative' = 'neutral'; | ||
| let foundNegativeKeyword = false; | ||
| let matchedKeyword = ''; | ||
|
|
||
| for (const keyword of negativeKeywords) { | ||
| if (messageText.includes(keyword.toLowerCase())) { | ||
| foundNegativeKeyword = true; | ||
| matchedKeyword = keyword; | ||
| sentiment = 'negative'; | ||
| break; | ||
| } | ||
| } | ||
|
|
||
| // Check for negative reactions (if available) | ||
| // This would require platform-specific reaction data in message.content | ||
| const negativeReactions = ['👎', '😠', '🚫', '❌', '🛑']; | ||
| const positiveReactions = ['👍', '❤️', '🔥', '😍', '🎉']; | ||
| const reactions = message.content?.reactions; | ||
| const hasNegativeReaction = Array.isArray(reactions) && | ||
| negativeReactions.some((emoji) => reactions.includes(emoji)); | ||
| const hasPositiveReaction = Array.isArray(reactions) && | ||
| positiveReactions.some((emoji) => reactions.includes(emoji)); | ||
|
|
||
| if (hasNegativeReaction) { | ||
| sentiment = 'negative'; | ||
| } else if (hasPositiveReaction) { | ||
| sentiment = 'positive'; | ||
| } |
There was a problem hiding this comment.
Prevent positive reactions from overriding negative keyword sentiment.
A negative keyword sets sentiment = 'negative', but a later positive reaction can overwrite it. This can skew learning toward positive even when feedback was negative.
🐛 Proposed fix
- if (hasNegativeReaction) {
- sentiment = 'negative';
- } else if (hasPositiveReaction) {
- sentiment = 'positive';
- }
+ if (hasNegativeReaction) {
+ sentiment = 'negative';
+ } else if (hasPositiveReaction && sentiment !== 'negative') {
+ sentiment = 'positive';
+ }📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| // Check message content for negative keywords | |
| const messageText = message.content?.text?.toLowerCase() || ''; | |
| let sentiment: 'positive' | 'neutral' | 'negative' = 'neutral'; | |
| let foundNegativeKeyword = false; | |
| let matchedKeyword = ''; | |
| for (const keyword of negativeKeywords) { | |
| if (messageText.includes(keyword.toLowerCase())) { | |
| foundNegativeKeyword = true; | |
| matchedKeyword = keyword; | |
| sentiment = 'negative'; | |
| break; | |
| } | |
| } | |
| // Check for negative reactions (if available) | |
| // This would require platform-specific reaction data in message.content | |
| const negativeReactions = ['👎', '😠', '🚫', '❌', '🛑']; | |
| const positiveReactions = ['👍', '❤️', '🔥', '😍', '🎉']; | |
| const reactions = message.content?.reactions; | |
| const hasNegativeReaction = Array.isArray(reactions) && | |
| negativeReactions.some((emoji) => reactions.includes(emoji)); | |
| const hasPositiveReaction = Array.isArray(reactions) && | |
| positiveReactions.some((emoji) => reactions.includes(emoji)); | |
| if (hasNegativeReaction) { | |
| sentiment = 'negative'; | |
| } else if (hasPositiveReaction) { | |
| sentiment = 'positive'; | |
| } | |
| // Check message content for negative keywords | |
| const messageText = message.content?.text?.toLowerCase() || ''; | |
| let sentiment: 'positive' | 'neutral' | 'negative' = 'neutral'; | |
| let foundNegativeKeyword = false; | |
| let matchedKeyword = ''; | |
| for (const keyword of negativeKeywords) { | |
| if (messageText.includes(keyword.toLowerCase())) { | |
| foundNegativeKeyword = true; | |
| matchedKeyword = keyword; | |
| sentiment = 'negative'; | |
| break; | |
| } | |
| } | |
| // Check for negative reactions (if available) | |
| const negativeReactions = ['👎', '😠', '🚫', '❌', '🛑']; | |
| const positiveReactions = ['👍', '❤️', '🔥', '😍', '🎉']; | |
| const reactions = message.content?.reactions; | |
| const hasNegativeReaction = Array.isArray(reactions) && | |
| negativeReactions.some((emoji) => reactions.includes(emoji)); | |
| const hasPositiveReaction = Array.isArray(reactions) && | |
| positiveReactions.some((emoji) => reactions.includes(emoji)); | |
| if (hasNegativeReaction) { | |
| sentiment = 'negative'; | |
| } else if (hasPositiveReaction && sentiment !== 'negative') { | |
| sentiment = 'positive'; | |
| } |
🤖 Prompt for AI Agents
In `@src/evaluators/attractSentinel.ts` around lines 166 - 194, The current logic
in the sentiment detection (variables messageText, negativeKeywords,
matchedKeyword, sentiment) allows a positive reaction (hasPositiveReaction) to
overwrite a previously detected negative keyword; change the reaction-handling
block so that negative reactions always set sentiment = 'negative' and positive
reactions set sentiment = 'positive' only if sentiment is not already 'negative'
(i.e., do not overwrite an existing negative sentiment from keywords or
reactions), preserving matchedKeyword when negative.
| private getResponseWindowMs(): number { | ||
| const settings = this.getSettings(); | ||
| return (settings as any).responseWindowMs || 30 * 60 * 1000; | ||
| } | ||
|
|
||
| /** | ||
| * Get conversion actions from settings (optional) | ||
| */ | ||
| private getConversionActions(): string[] { | ||
| const settings = this.getSettings(); | ||
| return (settings as any).conversionActions || []; | ||
| } |
There was a problem hiding this comment.
responseWindowMs / conversionActions settings are never read.
getResponseWindowMs() and getConversionActions() pull from getSettings(), but getSettings() never populates those fields. As a result, env/character config is ignored (conversion bonuses never apply; response window is always default).
✅ Proposed fix
return {
enabled: characterSettings.enabled ?? true,
allowedRooms: characterSettings.allowedRooms ?? this.parseEnvList('ATTRACT_ALLOWED_ROOMS'),
blockedRooms: characterSettings.blockedRooms ?? this.parseEnvList('ATTRACT_BLOCKED_ROOMS'),
minIdleHours,
cooldownHours,
minIdleMs: minIdleHours * 60 * 60 * 1000,
cooldownMs: cooldownHours * 60 * 60 * 1000,
sentimentDecayHours: characterSettings.sentimentDecayHours ?? this.parseEnvNumber('ATTRACT_SENTIMENT_DECAY_HOURS', 2),
graveyardDays: characterSettings.graveyardDays ?? this.parseEnvNumber('ATTRACT_GRAVEYARD_DAYS', 7),
strikeLimit: characterSettings.strikeLimit ?? this.parseEnvNumber('ATTRACT_STRIKE_LIMIT', 2),
behaviorsOrder: characterSettings.behaviorsOrder ?? ['reaction', 'tip', 'cta'] as AttractBehavior[],
globalDailyCap: characterSettings.globalDailyCap ?? this.parseEnvNumber('ATTRACT_GLOBAL_DAILY_CAP', 10),
negativeKeywords: characterSettings.negativeKeywords ?? this.parseEnvList('ATTRACT_NEGATIVE_KEYWORDS', 'shut up,be quiet,stop,mute,leave,go away'),
+ responseWindowMs: characterSettings.responseWindowMs ?? this.parseEnvNumber('ATTRACT_RESPONSE_WINDOW_MS', 30 * 60 * 1000),
+ conversionActions: characterSettings.conversionActions ?? this.parseEnvList('ATTRACT_CONVERSION_ACTIONS'),
};📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| private getResponseWindowMs(): number { | |
| const settings = this.getSettings(); | |
| return (settings as any).responseWindowMs || 30 * 60 * 1000; | |
| } | |
| /** | |
| * Get conversion actions from settings (optional) | |
| */ | |
| private getConversionActions(): string[] { | |
| const settings = this.getSettings(); | |
| return (settings as any).conversionActions || []; | |
| } | |
| return { | |
| enabled: characterSettings.enabled ?? true, | |
| allowedRooms: characterSettings.allowedRooms ?? this.parseEnvList('ATTRACT_ALLOWED_ROOMS'), | |
| blockedRooms: characterSettings.blockedRooms ?? this.parseEnvList('ATTRACT_BLOCKED_ROOMS'), | |
| minIdleHours, | |
| cooldownHours, | |
| minIdleMs: minIdleHours * 60 * 60 * 1000, | |
| cooldownMs: cooldownHours * 60 * 60 * 1000, | |
| sentimentDecayHours: characterSettings.sentimentDecayHours ?? this.parseEnvNumber('ATTRACT_SENTIMENT_DECAY_HOURS', 2), | |
| graveyardDays: characterSettings.graveyardDays ?? this.parseEnvNumber('ATTRACT_GRAVEYARD_DAYS', 7), | |
| strikeLimit: characterSettings.strikeLimit ?? this.parseEnvNumber('ATTRACT_STRIKE_LIMIT', 2), | |
| behaviorsOrder: characterSettings.behaviorsOrder ?? ['reaction', 'tip', 'cta'] as AttractBehavior[], | |
| globalDailyCap: characterSettings.globalDailyCap ?? this.parseEnvNumber('ATTRACT_GLOBAL_DAILY_CAP', 10), | |
| negativeKeywords: characterSettings.negativeKeywords ?? this.parseEnvList('ATTRACT_NEGATIVE_KEYWORDS', 'shut up,be quiet,stop,mute,leave,go away'), | |
| responseWindowMs: characterSettings.responseWindowMs ?? this.parseEnvNumber('ATTRACT_RESPONSE_WINDOW_MS', 30 * 60 * 1000), | |
| conversionActions: characterSettings.conversionActions ?? this.parseEnvList('ATTRACT_CONVERSION_ACTIONS'), | |
| }; |
🤖 Prompt for AI Agents
In `@src/services/attract.ts` around lines 953 - 964, getResponseWindowMs() and
getConversionActions() read fields that are never populated because
getSettings() doesn't merge the env/character config into the returned settings;
update getSettings() so it pulls/merges responseWindowMs and conversionActions
from the source config (e.g., character config or environment overrides) into
the settings object before returning. In practice, locate getSettings() and
ensure it copies/merges (responseWindowMs, conversionActions) from the canonical
config (e.g., this.character.config or process.env) so getResponseWindowMs(),
getConversionActions() see the configured values.
| "llm-api": 2 | ||
| }, | ||
| "currentRunnerIndex": 0 | ||
| } No newline at end of file |
There was a problem hiding this comment.
PR resolver state file accidentally committed to repo
Medium Severity
A 1173-line .pr-resolver-state.json file containing ephemeral PR review tooling state has been committed. This file includes iteration timestamps, comment verification tracking, model performance metrics, and other transient state from the prr tool. It does not belong in version control and will cause merge conflicts and confusion in future PRs.
There was a problem hiding this comment.
Actionable comments posted: 2
🤖 Fix all issues with AI agents
In `@src/evaluators/attractSentinel.ts`:
- Around line 19-34: Update the top-of-file evaluator docs in
src/evaluators/attractSentinel.ts to reflect the actual 30-minute strike window:
replace occurrences of "5 minutes" and the "WHY 5 MINUTE WINDOW FOR STRIKES"
paragraph with wording that states a 30-minute window and explains why 30
minutes (e.g., allows slightly delayed but still attributable feedback). Search
for the doc block around the attractSentinel evaluator (the header comment above
the evaluator implementation) and update those text strings so the docs match
the implementation's 30-minute validation window.
- Around line 212-216: The current guard "if (responses && responses.length >
0)" incorrectly prevents recording actions because the code only reads actions
from message.content?.actions; remove that conditional so the actions branch
always runs: locate the block using responses and actionsTriggered (variables:
responses, message, actionsTriggered) inside the AttractSentinel evaluator and
delete the outer responses check so you always compute const actionsTriggered =
message.content?.actions || [] and proceed to record/handle those actions
regardless of responses' presence or length.
| * WHEN IT RUNS: | ||
| * After any message in a tracked room, within 5 minutes of an attract. | ||
| * This window captures immediate reactions to the attract message. | ||
| * | ||
| * WHAT IT DOES: | ||
| * - Records replies (human vs agent, sentiment) | ||
| * - Records actions triggered by the agent's response | ||
| * - Applies strikes for negative feedback (keywords, reactions) | ||
| * | ||
| * WHY 5 MINUTE WINDOW FOR STRIKES: | ||
| * If someone says "shut up" 10 minutes after our attract, it might not be about us. | ||
| * 5 minutes is tight enough to be confident the feedback is about the attract. | ||
| * | ||
| * WHY 30 MINUTE WINDOW FOR ATTEMPTS (handled elsewhere): | ||
| * People take time to respond. "Oh I missed that, let me try" happens 15 min later. | ||
| * 30 minutes captures delayed engagement while staying attributable. |
There was a problem hiding this comment.
Update evaluator docs to match the 30‑minute window.
The implementation now validates and applies strikes within 30 minutes, but the header still says 5 minutes.
♻️ Proposed fix
- * After any message in a tracked room, within 5 minutes of an attract.
+ * After any message in a tracked room, within 30 minutes of an attract.
@@
- * WHY 5 MINUTE WINDOW FOR STRIKES:
- * If someone says "shut up" 10 minutes after our attract, it might not be about us.
- * 5 minutes is tight enough to be confident the feedback is about the attract.
+ * WHY 30 MINUTE WINDOW FOR STRIKES:
+ * If someone says "shut up" long after our attract, it might not be about us.
+ * 30 minutes balances attribution with delayed feedback.🤖 Prompt for AI Agents
In `@src/evaluators/attractSentinel.ts` around lines 19 - 34, Update the
top-of-file evaluator docs in src/evaluators/attractSentinel.ts to reflect the
actual 30-minute strike window: replace occurrences of "5 minutes" and the "WHY
5 MINUTE WINDOW FOR STRIKES" paragraph with wording that states a 30-minute
window and explains why 30 minutes (e.g., allows slightly delayed but still
attributable feedback). Search for the doc block around the attractSentinel
evaluator (the header comment above the evaluator implementation) and update
those text strings so the docs match the implementation's 30-minute validation
window.
| // Check if this message triggered any actions (from the user request) | ||
| // WHY: Actions are the real success metric. Someone saying "play jazz" triggers | ||
| // PLAY_AUDIO - that's what we want, not just "nice message". | ||
| if (responses && responses.length > 0) { | ||
| const actionsTriggered = message.content?.actions || []; |
There was a problem hiding this comment.
🧩 Analysis chain
🏁 Script executed:
cd /root/repo && git ls-files src/evaluators/attractSentinel.tsRepository: elizaos-plugins/plugin-attract
Length of output: 134
🏁 Script executed:
#!/bin/bash
# Check if file exists and explore the structure
if [ -f "src/evaluators/attractSentinel.ts" ]; then
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Remove the responses guard—actions are tracked from message.content?.actions regardless.
The block gates action recording on responses && responses.length > 0, but responses is never used inside the block. Actions are read exclusively from message.content?.actions, which is independent of whether responses exists. This causes action tracking to be skipped when responses is undefined or empty, even if meaningful actions are present on the message.
The guard should be removed entirely:
Suggested fix
- if (responses && responses.length > 0) {
- const actionsTriggered = message.content?.actions || [];
-
- if (Array.isArray(actionsTriggered) && actionsTriggered.length > 0) {
+ const actionsTriggered = message.content?.actions || [];
+ if (Array.isArray(actionsTriggered) && actionsTriggered.length > 0) {🤖 Prompt for AI Agents
In `@src/evaluators/attractSentinel.ts` around lines 212 - 216, The current guard
"if (responses && responses.length > 0)" incorrectly prevents recording actions
because the code only reads actions from message.content?.actions; remove that
conditional so the actions branch always runs: locate the block using responses
and actionsTriggered (variables: responses, message, actionsTriggered) inside
the AttractSentinel evaluator and delete the outer responses check so you always
compute const actionsTriggered = message.content?.actions || [] and proceed to
record/handle those actions regardless of responses' presence or length.
WHY: Time-based attracts (every X hours) feel robotic and can spam empty rooms. Reactive mode waits for actual presence before attracting. CHANGES: - Add triggerMode setting: 'reactive' (default) or 'immediate' - In reactive mode, room must be READY + someone shows up - Add reactiveDelayMs (30s default) to not interrupt immediately - Add maxReadyHours (24h default) fallback for reactive mode - Track readySince timestamp for fallback timeout - Add reactive attract queue processed every 30s - Update README with new configuration options FLOW (reactive mode): 1. Time-based: Room becomes READY (idle + cooldown satisfied) 2. Reactive: Wait for MESSAGE_RECEIVED in READY room 3. Queue room for attract after reactiveDelayMs delay 4. ATTRACT_LOOP processes queued rooms This makes attracts feel more natural - responding to presence, not a timer. Co-authored-by: Cursor <cursoragent@cursor.com>
WHY: Previous implementation waited for activity BEFORE first attract. The correct pattern is: drop bait first, THEN wait for response. CHANGES: - Add requiresReactiveTrigger flag to room tracking - Set flag when attract gets poor/no response (score <= 0) - Clear flag when activity is detected (someone shows up) - Queue reactive attract when activity clears the flag - First attract is always time-based (drop the bait) - Subsequent attracts require activity after failed bait FLOW: 1. Room becomes READY → attract (the bait) 2. If response: normal cooldown, repeat 3. If no response: set requiresReactiveTrigger 4. Wait for activity (trap to be sprung) 5. Activity detected → queue attract 6. Repeat from step 2 This prevents flooding unresponsive rooms while still proactively engaging. Co-authored-by: Cursor <cursoragent@cursor.com>
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Actionable comments posted: 3
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (2)
src/index.ts (1)
174-179:⚠️ Potential issue | 🟠 MajorDrop reactive‑queue entries when validation fails.
If a queued room fails validation, it stays in
reactiveAttractQueueand gets retried indefinitely. Removing it here avoids stuck entries and repeated validation churn.🔧 Proposed fix
if (!isValid) { logger.debug(`[Attract] Validation failed for room ${roomId}`); + attractService.removeFromReactiveQueue(roomId); continue; }src/services/attract.ts (1)
1445-1449:⚠️ Potential issue | 🟠 MajorClear
reactiveCheckIntervalinstop().Otherwise the reactive queue loop continues after the service stops.
🔧 Proposed fix
async stop(): Promise<void> { if (this.checkInterval) { clearInterval(this.checkInterval); this.checkInterval = null; } + if (this.reactiveCheckInterval) { + clearInterval(this.reactiveCheckInterval); + this.reactiveCheckInterval = null; + } logger.info('[Attract] AttractService stopped'); }
🤖 Fix all issues with AI agents
In `@README.md`:
- Around line 54-62: The fenced state-machine block currently has no language
hint; update the triple-backtick fence that wraps the diagram (the ASCII state
machine block) to include a language tag like text (i.e., change ``` to ```text)
so markdownlint stops flagging it and the block is treated as plain text.
- Around line 86-88: The scoring table row labels use unhyphenated compound
modifiers ("Human triggered action", "Conversion action bonus", "Agent triggered
action"); update those labels to use hyphens for correct compound modifiers —
change to "Human-triggered action", "Conversion-action bonus" (or
"Conversion-action bonus" if you prefer consistent hyphenation), and
"Agent-triggered action" in the README table so the grammar warnings are
resolved.
In `@src/services/attract.ts`:
- Around line 375-387: The code currently flips tracking.state to
RoomState.ACTIVE on any human message; modify the logic in the block guarded by
isFromThisAgent/isAttractMessage so that if tracking.state === RoomState.MUTED
you do not change state to ACTIVE (you may still update timestamps if desired),
i.e., add a guard around the lines that set tracking.state = RoomState.ACTIVE
and tracking.readySince = undefined so they only run when tracking.state !==
RoomState.MUTED; reference the symbols isFromThisAgent, isAttractMessage,
tracking, RoomState.READY, RoomState.MUTED, and the assignments to
tracking.lastHumanMessageAt, tracking.state, and tracking.readySince to locate
and update the code.
| ``` | ||
| ACTIVE ──(idle N hours)──> IDLE ──(cooldown ok)──> READY ──(attract sent)──> ACTIVE | ||
| ↑ | | ||
| └──────────(2+ strikes)──────> MUTED <──────────────┘ | ||
| ACTIVE ──(idle N hours)──> IDLE ──(cooldown ok)──> READY | ||
| ↑ │ | ||
| │ Reactive mode: wait for activity trigger ←───┤ | ||
| │ │ | ||
| └──────────────(attract sent)─────────────────────┘ | ||
|
|
||
| ANY ──(2+ strikes)──> MUTED | ||
| ``` |
There was a problem hiding this comment.
Add a language hint for the state-machine block.
markdownlint flags the fence without a language; mark it as plain text.
🔧 Proposed fix
-```
+```text📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| ``` | |
| ACTIVE ──(idle N hours)──> IDLE ──(cooldown ok)──> READY ──(attract sent)──> ACTIVE | |
| ↑ | | |
| └──────────(2+ strikes)──────> MUTED <──────────────┘ | |
| ACTIVE ──(idle N hours)──> IDLE ──(cooldown ok)──> READY | |
| ↑ │ | |
| │ Reactive mode: wait for activity trigger ←───┤ | |
| │ │ | |
| └──────────────(attract sent)─────────────────────┘ | |
| ANY ──(2+ strikes)──> MUTED | |
| ``` |
🧰 Tools
🪛 markdownlint-cli2 (0.20.0)
[warning] 54-54: Fenced code blocks should have a language specified
(MD040, fenced-code-language)
🤖 Prompt for AI Agents
In `@README.md` around lines 54 - 62, The fenced state-machine block currently has
no language hint; update the triple-backtick fence that wraps the diagram (the
ASCII state machine block) to include a language tag like text (i.e., change ```
to ```text) so markdownlint stops flagging it and the block is treated as plain
text.
| | Human triggered action | 10 | Primary goal - someone used a capability | | ||
| | Conversion action bonus | +10 | Operator-defined high value (sales, tips) | | ||
| | Agent triggered action | 3 | Multi-agent coordination, mild success | |
There was a problem hiding this comment.
Hyphenate compound modifiers in the scoring table.
This resolves the grammar warnings in the row labels.
✍️ Proposed fix
-| Human triggered action | 10 | Primary goal - someone used a capability |
+| Human-triggered action | 10 | Primary goal - someone used a capability |
-| Agent triggered action | 3 | Multi-agent coordination, mild success |
+| Agent-triggered action | 3 | Multi-agent coordination, mild success |📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| | Human triggered action | 10 | Primary goal - someone used a capability | | |
| | Conversion action bonus | +10 | Operator-defined high value (sales, tips) | | |
| | Agent triggered action | 3 | Multi-agent coordination, mild success | | |
| | Human-triggered action | 10 | Primary goal - someone used a capability | | |
| | Conversion action bonus | +10 | Operator-defined high value (sales, tips) | | |
| | Agent-triggered action | 3 | Multi-agent coordination, mild success | |
🧰 Tools
🪛 LanguageTool
[grammar] ~86-~86: Use a hyphen to join words.
Context: ...|---------|--------|-----------| | Human triggered action | 10 | Primary goal - s...
(QB_NEW_EN_HYPHEN)
[grammar] ~88-~88: Use a hyphen to join words.
Context: ...fined high value (sales, tips) | | Agent triggered action | 3 | Multi-agent coord...
(QB_NEW_EN_HYPHEN)
🤖 Prompt for AI Agents
In `@README.md` around lines 86 - 88, The scoring table row labels use
unhyphenated compound modifiers ("Human triggered action", "Conversion action
bonus", "Agent triggered action"); update those labels to use hyphens for
correct compound modifiers — change to "Human-triggered action",
"Conversion-action bonus" (or "Conversion-action bonus" if you prefer consistent
hyphenation), and "Agent-triggered action" in the README table so the grammar
warnings are resolved.
src/services/attract.ts
Outdated
| if (!isFromThisAgent && !isAttractMessage) { | ||
| const settings = this.getSettings(); | ||
|
|
||
| // REACTIVE TRIGGER: If room was READY and someone just arrived, that's the trigger! | ||
| // WHY: Time-based conditions are met (idle + cooldown). Now someone showed up. | ||
| // This is the moment to engage - not a random timer, but actual presence. | ||
| const wasReady = tracking.state === RoomState.READY; | ||
|
|
||
| // Update tracking state | ||
| tracking.lastHumanMessageAt = Date.now(); | ||
| tracking.state = RoomState.ACTIVE; | ||
| tracking.readySince = undefined; | ||
|
|
There was a problem hiding this comment.
Muted rooms are reactivated on any human message.
Line 384 resets state to ACTIVE even when MUTED, which undermines the mute semantics.
🔧 Proposed fix
if (!isFromThisAgent && !isAttractMessage) {
+ if (tracking.state === RoomState.MUTED) {
+ tracking.lastHumanMessageAt = Date.now();
+ return;
+ }
const settings = this.getSettings();🤖 Prompt for AI Agents
In `@src/services/attract.ts` around lines 375 - 387, The code currently flips
tracking.state to RoomState.ACTIVE on any human message; modify the logic in the
block guarded by isFromThisAgent/isAttractMessage so that if tracking.state ===
RoomState.MUTED you do not change state to ACTIVE (you may still update
timestamps if desired), i.e., add a guard around the lines that set
tracking.state = RoomState.ACTIVE and tracking.readySince = undefined so they
only run when tracking.state !== RoomState.MUTED; reference the symbols
isFromThisAgent, isAttractMessage, tracking, RoomState.READY, RoomState.MUTED,
and the assignments to tracking.lastHumanMessageAt, tracking.state, and
tracking.readySince to locate and update the code.
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Actionable comments posted: 0
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (2)
src/services/attract.ts (2)
1470-1476:⚠️ Potential issue | 🟡 MinorMissing cleanup of reactive check interval in
stop()method.The
stop()method clearscheckIntervalbut doesn't clearreactiveCheckInterval, which could cause the reactive loop to continue running after the service is stopped.🔧 Proposed fix
async stop(): Promise<void> { if (this.checkInterval) { clearInterval(this.checkInterval); this.checkInterval = null; } + if (this.reactiveCheckInterval) { + clearInterval(this.reactiveCheckInterval); + this.reactiveCheckInterval = null; + } logger.info('[Attract] AttractService stopped'); }
796-827:⚠️ Potential issue | 🟡 MinorUnfiltered
attract_historyquery creates duplicate entries in recent attracts list.
recordAttract()persists withtype: 'attract', andfinalizeAttempt()persists the same message withtype: 'attract_attempt'to the same table. WhilegetAttemptHistory()correctly filters bytype === 'attract_attempt',getRecentAttracts()does not filter by type—it retrieves all entries matching the room and entityId. This causes the same message text to appear twice in the recent attracts list: once from the initialrecordAttract()call and again from the attempt finalization. Consider adding&& m.content?.type === 'attract'to the filter ingetRecentAttracts()to exclude attempt records, or consolidate to a single persistence point.
🧹 Nitpick comments (1)
src/services/attract.ts (1)
31-41: Reactive check loop only logs status; actual processing happens elsewhere.The
processReactiveQueue()method (Lines 459-477) only logs diagnostic info about the queue state. The actual processing happens whenATTRACT_LOOPcallsgetReactiveAttractRooms(). This is fine but could be confusing - consider adding a comment instartReactiveCheckLoop()clarifying that the loop is for diagnostics only, or remove the loop entirely if the logging isn't essential.Also applies to: 440-452, 459-477
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Cursor Bugbot has reviewed your changes and found 1 potential issue.
Bugbot Autofix is OFF. To automatically fix reported issues with Cloud Agents, enable Autofix in the Cursor dashboard.
| } | ||
| } | ||
| } | ||
|
|
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Missing interval cleanup causes resource leak on service stop
Medium Severity
The stop() method clears checkInterval but not reactiveCheckInterval. The PR adds a new interval via startReactiveCheckLoop() (line 445) that runs every 5 seconds, but the stop() method was not updated to clear it. When the service stops, this interval continues running, causing a resource leak and potentially accessing service state after shutdown. The fix requires adding if (this.reactiveCheckInterval) { clearInterval(this.reactiveCheckInterval); this.reactiveCheckInterval = null; } to the stop() method.
Additional Locations (1)
1 participant
…tion
Note
Medium Risk
Moderate risk because it changes core attract scheduling/trigger behavior, adds new in-memory+DB persistence for attempts, and expands evaluator tracking windows, which could affect message frequency and data recorded per room.
Overview
Adds a closed-loop “attempt” learning system: each attract creates an in-memory
AttractAttempt, the evaluator records replies/actions/sentiment during a 30‑minute window, and the service finalizes and persists scored attempts toattract_historyfor reuse in future prompts.Introduces reactive “bait & wait” triggering (default) with a reactive queue/delay, fallback after
maxReadyHours, and updated loop scheduling/room selection to process both time-ready and reactive-triggered rooms.Updates prompting and UX: the provider formats and injects attempt history into
attractTemplate, fixes history/cold-start display, improves outcome formatting (incl. agent actions), and adjustsattractActionflow (finalize only expired attempts, enforce callback before recording state, setmaxTokens: 300, and treat"..."as an opt-out with retry). Documentation is significantly expanded inREADME.md, and PRR metadata/lessons files are added.Written by Cursor Bugbot for commit 40dc5c1. This will update automatically on new commits. Configure here.
Summary by CodeRabbit
Release Notes
New Features
Documentation
Greptile Summary
This PR implements a closed-loop learning system for the attract plugin, enabling the agent to learn from past attempts through in-context pattern matching.
Key Changes:
AttractAttemptinterface to track outcomes: replies, actions triggered, sentiment, and calculated scorescreateAttempt→recordReply→recordActionsTriggered→finalizeAttemptattractSentinelevaluator to monitor the 30-minute response window and record engagement metricsDesign Philosophy:
LLMs don't learn between calls, but they can pattern-match in-context. By showing "this message got 10pts (PLAY_AUDIO triggered)", the LLM infers what works without explicit technique categorization.
Issues Found:
createAttemptandfinalizeAttemptcauses overwritesConfidence Score: 3/5
src/evaluators/attractSentinel.ts(action extraction logic) andsrc/services/attract.ts(duplicate persistence and finalization timing)Important Files Changed
Sequence Diagram
sequenceDiagram participant User participant AttractAction participant AttractService participant LLM participant AttractSentinel Note over AttractAction,AttractService: Attract Message Sent AttractAction->>AttractService: finalizeAttempt(roomId) Note right of AttractService: Close previous learning loop AttractService->>AttractService: calculateScore(attempt) AttractService->>AttractService: persist to DB AttractAction->>LLM: Generate attract message Note right of LLM: Sees history: "10pts", "0pts" LLM-->>AttractAction: "anyone need something played?" AttractAction->>AttractService: recordAttract(roomId, message) AttractAction->>AttractService: createAttempt(roomId, message) Note right of AttractService: Start 30min tracking window AttractService->>AttractService: Store pending attempt Note over User,AttractSentinel: Users Respond (30min window) User->>AttractSentinel: "yeah play jazz" AttractSentinel->>AttractService: recordReply(roomId, isHuman, sentiment) AttractSentinel->>AttractService: recordActionsTriggered(roomId, isHuman, [PLAY_AUDIO]) Note right of AttractService: Human action = 10pts User->>AttractSentinel: "thanks!" AttractSentinel->>AttractService: recordReply(roomId, isHuman, positive) Note right of AttractService: Reply without action = +1pt Note over AttractService: Window Expires (30min later) AttractService->>AttractService: finalizeAttempt(roomId) AttractService->>AttractService: score = 10 (action) + 1 (reply) = 11pts AttractService->>AttractService: persist finalized attempt Note over AttractAction,LLM: Next Attract (shows history) AttractAction->>LLM: Generate with history Note right of LLM: Sees: "anyone need something played?" → 11pts LLM-->>AttractAction: Pattern-matches successful approach