Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ash1794/vibe-engineering --skill reflect-and-compoundgit clone --depth 1 https://github.com/ash1794/vibe-engineeringWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ash1794/vibe-engineering/reflect-and-compound)<a href="https://agentmods.dev/skills/ash1794/vibe-engineering/reflect-and-compound"><img src="https://agentmods.dev/badge/skills/ash1794/vibe-engineering/reflect-and-compound/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ash1794/vibe-engineering/reflect-and-compound"><img src="https://agentmods.dev/badge/skills/ash1794/vibe-engineering/reflect-and-compound.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.00563 |
| Opus 5 | $0.00022 | $0.00282 |
| Sonnet 5 | $0.00009 | $0.00113 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
vibe-reflect-and-compound scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- vibe-reflect-and-compound — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Project learnings file (e.g.,
-
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]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 70 lines · 44 tokens per session scan A 04b7218e04da
vibe-reflect-and-compound is a skill published in the GitHub repository ash1794/vibe-engineering (10 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 563 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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