temporal-forensics
Skill1 starsChanged 8 months agoMITView on GitHub
Team D diagnostic — temporal analysis for intermittent issues. Hunts race conditions, stale state, cache timing, and async ordering.
In this repository51 other files it gives its agents.
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- consultSkill
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- evolveSkill
- frontend-designSkill
- full-stack-buildSkill
- full-stack-traceSkill
- gh-repo-reconSkill
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- skill-auditSkill
- skill-creatorSkill
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The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
When the issue occurs vs when it doesn't (if known)
- Distinctive: line 97
If no timing pattern found: escalate to Team E (might be a regression — something changed recently).
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Temporal Forensics (Team D)
For intermittent issues that come and go, or that seemed fixed but returned. The problem is timing-dependent — this team finds the timing.
When to Use
- Directly: when the issue is intermittent or timing-related
- Via router:
/persistent-issueclassifies as Category D
Input
- Evidence Document from
/persistent-issue - When the issue occurs vs when it doesn't (if known)
Agent Team (Fan-Out/Fan-In, all model: "opus")
Dispatch 3 agents simultaneously:
Agent 1: Race Condition Hunter
Search for race conditions and async ordering issues.
Evidence: [paste Evidence Document]
Check these patterns in the affected code:
1. **useEffect ordering**: Are multiple useEffects competing for the same state?
- Check deps arrays — are they stable? (object/array refs change every render)
- Is there a useEffect that sets state that triggers another useEffect?
2. **Concurrent fetches**: Are multiple API calls racing?
- Check if responses can arrive out of order
- Check if a slow response overwrites a fast one
3. **State updates during unmount**: Is a component setting state after unmounting?
- Check for missing cleanup in useEffect return
4. **Cache read-after-write**: Is code reading cache immediately after writing?
- Eventually consistent stores may return stale data after immediate writes
5. **API rate limits**: Are concurrent mutations exhausting budget?
- Check for parallel mutations without rate limiting
Output: Specific race condition with timing diagram showing the failure pathAgent 2: Stale State Detective
Search for stale data, expired caches, and closure captures.
Evidence: [paste Evidence Document]
Check:
1. **Cache TTL**: Is the cache TTL too long? Too short?
- Is the issue that data is correct in source but stale in cache?
2. **localStorage**: Is the app reading old localStorage data?
- Column settings, tab preferences, toggles
- Cross-reference saved values against current defaults
3. **React closures**: Is a callback capturing stale state?
- Check useCallback deps — missing deps means stale closure
- Check event handlers defined inside render without useCallback
4. **Sync lag**: Do background sync processes run at intervals?
- Is the user expecting immediate updates that won't appear until next sync?
5. **Cache format mismatch**: Is code reading cache without proper deserialization?
- Compressed cache keys read without decompression return garbage
6. **Browser cache**: Is the browser serving a stale JavaScript bundle?
- Check if content hashing is working (filenames should have hashes)
Output: Specific stale state source + what triggers the stalenessAgent 3: Timing Profiler
Analyze timing correlations.
Evidence: [paste Evidence Document]
Check:
1. **Cron timing**: Does the issue correlate with scheduled task schedules?
- Check all cron intervals and their UTC offsets
- Account for DST changes (UTC-only schedules shift relative to local time)
2. **Deploy timing**: Did the issue appear right after a deploy?
- Secret changes can unregister cron triggers in some platforms
- Build artifacts might be stale (deployed from wrong directory?)
3. **Cache expiry window**: Does the issue appear at specific intervals?
- Map intervals to known cache TTLs and sync frequencies
4. **User session timing**: Does it happen after being idle?
- Auth token expiry
- localStorage TTL checks
Output: Timing pattern identified + correlation with specific system eventSynthesis
Main agent merges timing findings: "The issue is intermittent because [timing condition]. It manifests when [trigger A] coincides with [state B]. The fix is [make the timing deterministic / extend TTL / add retry / fix the race]."
If no timing pattern found: escalate to Team E (might be a regression — something changed recently).
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