Chalk Labs
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Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
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/maroffo-learning-docs
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/learning-docs
What's inside
- Skill name
learning-docs- Description
- Create and update LEARNING.md project retrospectives. Use when user says retrospective, lessons learned, what did we learn, document decisions, or session analysis.
- License
- MIT
- Instructions
- 139 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# ABOUTME: Project knowledge capture through engaging LEARNING.md files # ABOUTME: Documents architecture, decisions, bugs, lessons learned in conversational style # Learning Documentation ## Quality Notes - Quality of insights matters more than covering every change - Re-read what you wrote: is it useful to a future reader, or just filler? ## Purpose Capture project knowledge in `LEARNING.md` - a living document that grows with the project. Not boring docs, but engaging technical storytelling. ## When to Update - After fixing non-trivial bugs - After architectural decisions - After integrating new tech - After solving tricky problems - Before context switches (end of day/week) ## Structure Sections: **Project Overview**, **Architecture** (mermaid diagrams), **Tech Stack & Decisions** (table: Technology | Why | Trade-offs), **Lessons Learned** (dated: Context → Problem → Solution → Takeaway), **Pitfalls & Gotchas**, **Best Practices Discovered** ## Writing Style | Do | Don't | |----|-------| | Conversational tone | Dry technical prose | | Analogies that clarify | Jargon without context | | Concrete examples | Abstract descriptions | | "We tried X, it broke because Y" | "X is not recommended" | | Honest about mistakes | Sanitized corporate-speak | ## Examples Illustrative only: every fact in a lesson (durations, numbers, causes, fixes) comes from the session, the git history, or the user. When a detail is unknown, leave it out or ask; never invent one to make the story vivid. **Good:** > We spent 2 hours debugging why webhooks weren't firing. Turns out Redis was silently dropping messages when memory hit 80%. Added `maxmemory-policy volatile-lru` and monitoring. Lesson: always monitor your message queues, silence is not golden. **Bad:** > Webhook reliability was improved by adjusting Redis configuration parameters. ## Workflow 1. **Read** existing LEARNING.md (or create if missing) 2. **Review** recent work (`git log --oneline -10`) 3. **Ask** what was learned, what was tricky 4. **Append** new lessons in conversational style (dated, searchable) 5. **Capture solutions** in `docs/solutions/[category]/` for searchable reuse 6. **Mirror lessons to vault** (below): cross-project archive, blog discovery, knowledge-sync input **Vault copy (lessons):** after appending to LEARNING.md, also append each new lesson to the vault (create the note first with `obsidian create name="<project> - Learnings" silent` if missing; command syntax in `_OBSIDIAN.md`): ```bash obsidian append file="<project> - Learnings" content="### YYYY-MM-DD: <title>\n<Context → Problem → Solution → Takeaway, condensed to a few lines>" ``` The repo's LEARNING.md stays the source of truth. If the obsidian CLI is unavailable, skip (do not use the path fallback; the repo copy is authoritative). **Vault privacy (applies to EVERY vault copy in this skill: lessons, solutions, skill candidates):** for work projects (HikmaAI, client repos), mirror only content safe outside the work perimeter. Exclude client names, internal hostnames and architecture details, unreleased product information, anything under NDA. When in doubt, keep it repo-only. ## Solutions Directory For solved problems worth referencing again, create files in `docs/solutions/`: ``` docs/solutions/ ├── auth/ → Authentication, authorization, sessions ├── performance/ → Profiling, caching, optimization ├── infrastructure/ → CI/CD, Docker, deployment ├── database/ → Migrations, queries, indexing ├── testing/ → Patterns, fixtures, flaky test fixes └── debugging/ → Hard bugs, investigation techniques ``` **Format:** `docs/solutions/[category]/YYYY-MM-DD_short-description.md` Each solution file: ```markdown # Problem [What broke / what we needed] # Solution [What fixed it, with code if relevant] # Why It Works [Root cause or design rationale, 1-3 sentences] ``` **When to use LEARNING.md vs solutions/**: LEARNING.md for narrative retrospectives, architectural decisions, broad lessons. Solutions/ for specific, searchable, reusable fixes; "how did we solve X?" answers. **Vault copy:** After writing to `docs/solutions/`, also append to vault: `obsidian append file="<project> - Solutions" content="### YYYY-MM-DD: [title]\n[Problem/Solution/Why]"`. Creates cross-project discoverability. ## Session Analysis Analyze past sessions to identify improvement opportunities. Session files live in `~/.claude/projects/` (project paths: slashes→dashes). ### Extraction Session files run to 100k+ lines, so extract summaries with jq instead of reading them raw, and look for patterns rather than individual messages. ### What to Look For | Pattern | Example | Fix | |---------|---------|-----| | Token waste | Read same file 5+ times | Cache key info, update CLAUDE.md | | Wrong paths | Built feature, then found existing code | Better initial search, architecture docs | | Repeated mistakes | Same lint error 3 sessions | Pre-commit hook, CLAUDE.md note | | Missing automation | Manual steps every session | Script it, add to workflow | | Context loss | Re-learn after compaction | Save state to LEARNING.md before limit | ### Key jq Commands Sessions live in `~/.claude/projects/PROJECT_NAME/<session-id>.jsonl`, one event per line; message content sits under `.message.content`.
From maroffo/claude-forge, MIT.
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Signals
- Stars
- 17
- Forks
- 1
- Open issues
- 6
- Last commit (this folder)
- Sep 23, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/maroffo/claude-forge
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Git conventions for commit messages and workflow.
SkillAFreshness: A★ 17Claude Code +9 - 0.606score
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PR-level review that composes gemini-review, the orchestrator review fleet, and (when contested) second-opinion, reading each commit's intent before judging.
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Execution trace capture and token baselining.
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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learning-docs skill. Agent Mart. https://agentmart.dev/skills/maroffo-learning-docs (last updated 2026-10-24)