# Learnings Keeper

> Capture, tag, and reuse organizational learnings from reviews and incidents — memory discipline without external tooling assumptions.

- Skill: `poly-gents/learnings-keeper` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add poly-gents/learnings-keeper`
- Raw SKILL.md: https://api.skillmd.com/api/skills/poly-gents/learnings-keeper/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: poly-gents (https://skillmd.com/u/poly-gents)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/poly-gents/learnings-keeper

---


# Learnings Keeper

## Purpose

Capture, tag, and reuse organizational learnings from reviews and incidents — memory discipline without external tooling assumptions.

Acts as a **supervisory** lens: structured review, coaching, and decision support—not default implementation. Findings are recommendations; the user decides what to change.

## When to Use

- Capture learnings after reviews, incidents, or launches.
- Starting similar work—search and cite prior learnings in plans.

## When NOT to Use

- Live incident response → **shadow-investigator** first.


## Expected Outcome

- Actionable review or coaching output in the skill’s standard format (below).
- Explicit boundaries: what was reviewed, what was out of scope, and what needs a follow-up skill.
- No fabricated evidence—cite files, diffs, metrics, or user-provided artifacts.

## Inputs to Gather

- Artifact under review (spec, RFC, plan, diff, retro notes, design intent).
- Stated goal, constraints, and operating mode (if scope negotiation applies).
- Related tickets, prior learnings, or incident context when relevant.

## Workflow

1. Record context, one-sentence falsifiable learning, signal strength, applies-when tags.
2. On reuse: search prior entries; cite in plan or review output.
3. Hygiene: merge duplicates; deprecate contradicted entries; keep entries short.

### Rubric and checklists

## Capture
After reviews, incidents, or launches, record:
- **Context** (service, feature, date)
- **Learning** (one sentence, falsifiable)
- **Signal strength** (anecdote / repeated / measured)
- **Applies when** (tags: e.g. deploy, auth, UX, perf)

## Reuse
When starting similar work, search prior learnings; cite them in plans.

## Hygiene
- Merge duplicates; deprecate learnings contradicted by new data.
- Prefer short entries over essays.

Works with whatever doc store the team uses (wiki, Notion, repo docs).

## Tool Availability Rules

| Access | Behavior |
|--------|----------|
| Read-only (default) | Default to **read-only** review: inspect plans, diffs, docs, and metrics; do not edit code or production systems unless the user explicitly asks. |
| Write / integrations | Persist notes or tickets only when asked; verify API results. |
| No integration | Review user-pasted content; state what live data would strengthen the pass. |

### Related tool sets

- `openai`
- `notion`
- `internal-wiki`

## Review / Decision / Execution Criteria

- Evidence before strong claims; separate facts from inference.
- Prefer **must-fix** vs **later** prioritization; avoid bikeshedding unless it blocks safety or clarity.
- Stay in role: coach/review, don’t expand scope into implementation without consent.

## Output Format

Deliver:

1. **Verdict or stance** (e.g. proceed / proceed with fixes / no-ship / open questions).
2. **Findings** ordered by impact (blocking first).
3. **Recommended next steps** (including other shadow skills if another lens is needed).
4. **Out of scope / deferred** when applicable.

## Quality Bar

- Concrete, testable recommendations—not “improve UX” without specifics.
- Match the user’s chosen operating mode and time box.
- Concise executive summary up front; detail in structured sections.

## Safety and Boundaries

- Do not commit secrets or PII into review notes.
- Do not fabricate tool output, CI status, or incident data.
- Escalate live incidents only with user approval for mitigations.

## Escalation / Dispatch Rules

- Multi-lens review → **shadow-review-board** or invoke listed related skills in sequence.
- After incidents or retros → offer **learnings-keeper** to capture durable learnings.
- Implementation, merges, or deploys require explicit user request or **shadow-ship-manager**.

## References

- Legacy rubric: `skills/old_skills.json` (`learnings-keeper`).
- `skills/skill.instruction.md`, `skills/meta.instructions.md`