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Vibe Reflect And Compound

skill-ash1794-vibe-engineering-reflect-and-compound · by ash1794

Extracts learnings from completed work, feedback, or failures. Updates a persistent learnings file with capped entries. Use after receiving feedback, fixing bugs, or completing complex tasks.

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Install

$ agentstack add skill-ash1794-vibe-engineering-reflect-and-compound

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

vibe-reflect-and-compound

Every problem solved should produce reusable knowledge. Don't just fix — learn.

When to Use This Skill

  • After receiving feedback on your work (positive or negative)
  • After a failed attempt or debugging session
  • After completing a complex task
  • After a code review with substantive feedback
  • Periodically (e.g., end of week) to consolidate learnings

When NOT to Use This Skill

  • After trivial tasks (typo fixes, simple renames)
  • When there's nothing new to learn (routine work)
  • During active implementation (reflect AFTER, not DURING)

Steps

  1. Gather input — What happened?
  • What was the task/feedback/failure?
  • What was expected vs. what actually happened?
  • What was the root cause?
  1. Extract patterns — Ask:
  • "What would I do differently next time?"
  • "What pattern does this represent?"
  • "Is this a recurring theme?"
  • "What would have caught this earlier?"
  1. Formulate learnings — Each learning should be:
  • Actionable — Not "be careful" but "always run race detection before committing concurrent code"
  • Specific — Not "tests are important" but "property-based tests catch edge cases that table-driven tests miss for parser code"
  • Contextual — Include when it applies and when it doesn't
  1. Update persistent storage — Write to:
  • Project learnings file (e.g., docs/learnings.md or LEARNINGS.md)
  • Claude memory (if available)
  • Team wiki/docs
  1. Cap management — Keep max 30 active learnings. When exceeding:
  • Archive older learnings to a dated file
  • Keep only the most frequently referenced ones active
  • Merge similar learnings

Output Format

Reflection: [Context]

Trigger: [What prompted this reflection]

Learnings Extracted:

  1. [Pattern name]: [Actionable learning]
  • Applies when: [context]
  • Evidence: [what happened]
  1. [Pattern name]: [Actionable learning]
  • Applies when: [context]
  • Evidence: [what happened]

Updated: [Where learnings were saved] Active Count: X/30

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.