agent-learn
Captures learnings after a feature or incident completes.
Skill by queen-of-code
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/queen-of-code-agent-learn
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About
Use cases: productivity, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/agent-learn
What's inside
- Skill name
agent-learn- Description
- Captures learnings after a feature or incident completes. Updates PROJECT.md, writes or updates ADRs, adds retrospective notes to Tech Specs, and updates repo documentation so future agents start with current context.
- License
- MIT
- Instructions
- 73 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Learn Agent The Learn agent runs as part of the AIDLC Validate+Learn phase after a feature passes validation, or as part of Close+Learn after an incident is resolved. Its job is to ensure that everything discovered during the cycle is captured in durable, agent-readable form so future work starts with full context. ## When to Invoke - After a Feature passes Validate (development lifecycle) - After an Incident passes Close (operational lifecycle) - After any significant architectural decision that needs an ADR ## Responsibilities ### 1. Update PROJECT.md (Required) The project memory file (`PROJECT.md` at repo root) is the quick-reference context document that all agents read at the start of a session. After every feature completion, the Learn agent must update it: - **Add the feature** to the "Implemented Features" section with: - Feature number and title (linked to the GitHub issue) - Current status - A 2–3 sentence description of what was built and why - Sub-issues completed (linked to their GitHub issues) - Key technical decisions made during implementation - **Update "Last updated" date** in the header - **Update the Architecture Overview** if the feature changed the deployment stack, added services, or modified the directory structure - **Update Conventions** if the feature established new patterns or changed existing ones ### 2. Write or Update ADRs (If Applicable) If the feature involved significant architectural decisions — new services, technology choices, protocol decisions, schema changes — write an ADR capturing: - The context and problem - Options considered - The decision and rationale - Consequences and trade-offs ADRs go in repo-root **`adr/`**, named `NNNN-title-with-dashes.md`. Copy from the bundled template [`spec-management/templates/adr-template.md`](../../spec-management/templates/adr-template.md) and read [`adr-guidance.md`](../../spec-management/templates/adr-guidance.md) for naming and when to write one. ### 3. Retrospective Notes on Tech Specs (If Applicable) For each Tech Spec (Unit) in the feature, add a brief retrospective note at the bottom capturing: - What differed from the plan and why - Anything that was harder or easier than expected - Patterns discovered that should inform future specs ### 4. Update Repo Documentation (If Applicable) If the feature changed how things work in ways that affect onboarding or day-to-day development: - Update `README.md` if top-level structure or quickstart changed - Update `docs/` files if specific documentation areas are affected - Update `AGENTS.md` if agent/skill discoverability changed ### 5. Note Process Friction (If Applicable) If the AIDLC process itself had friction during this cycle, note it in a brief section at the bottom of the feature's retrospective. This feeds back into AIDLC process improvement. ## Output Format The Learn agent produces a single commit (or PR) containing all documentation updates. The commit message follows the convention: ``` docs(learn): capture learnings from Feature #<N> — <title> ``` ## Quality Criteria - PROJECT.md accurately reflects the current state of the project after the feature - A new agent starting a session and reading only PROJECT.md would have enough context to understand what exists, where it runs, and what decisions were made - No stale information remains from before the feature was implemented - ADRs, if written, are self-contained and don't require reading the full PR history to understand
From queen-of-code/AI-DLC, MIT.
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Signals
- Stars
- 9
- Forks
- 13
- Open issues
- 0
- Last commit (this folder)
- Apr 13, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/queen-of-code/AI-DLC
- Website
- queenofcode.dev
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
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Cite this page
agent-learn skill. Agent Mart. https://agentmart.dev/skills/queen-of-code-agent-learn (last updated 2026-10-24)