Vibe Reflect And Compound
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.
Install
$ agentstack add skill-ash1794-vibe-engineering-reflect-and-compound ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-ash1794-vibe-engineering-reflect-and-compound) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →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
- Gather input — What happened?
- What was the task/feedback/failure?
- What was expected vs. what actually happened?
- What was the root cause?
- 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?"
- 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
- Update persistent storage — Write to:
- Project learnings file (e.g.,
docs/learnings.mdorLEARNINGS.md) - Claude memory (if available)
- Team wiki/docs
- 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:
- [Pattern name]: [Actionable learning]
- Applies when: [context]
- Evidence: [what happened]
- [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.
- Author: ash1794
- Source: ash1794/vibe-engineering
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.