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 agentmods add commands/sefaertunc/worclaude/learngit clone --depth 1 https://github.com/sefaertunc/WorclaudeWhat 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 | $0.00009 | $0.00843 |
| Opus 5 | $0.00005 | $0.00421 |
| Sonnet 5 | $0.00002 | $0.00169 |
| Haiku 4.5 | $0.00001 | $0.00084 |
Grade A, and why
learn 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user wants to capture a learning from this session.
When invoked with arguments, use them as the learning to capture.
Example: /learn Always use conventional commits for this project
If no arguments provided, ask the user what they want to remember.
Format
A learning is a [LEARN] block:
[LEARN] Category: One-line rule description
Mistake: What went wrong (optional)
Correction: What should happen instead (optional)
Write to .claude/learnings/{category-slug}.md with YAML frontmatter:
---
created: <today's date YYYY-MM-DD>
category: <from the [LEARN] block>
project: <package.json name, or directory name as fallback>
---
Do NOT add a times_applied field. The auto-capture hook never
increments it; the field would be a lie. Removed in Phase 2 (2026-04).
After writing, regenerate .claude/learnings/index.json from the
directory contents — never hand-maintain it. The regeneration walks
.claude/learnings/*.md, parses each frontmatter, and writes the
canonical { "learnings": [{file, category, created}, ...] } index.
This guarantees the index never drifts from the files on disk.
Confirm to the user what was saved and where.
When to use /learn vs other memory layers
The system has multiple memory layers; pick the right one for the trigger:
| Trigger | Lands in | Audience |
|---|---|---|
| Plain conversation ("user pushes back") | Claude Code's auto-memory (autonomous) | Personal, machine-local |
/learn or [LEARN] marker |
.claude/learnings/ |
Team-relevant |
/update-claude-md (later promotion path) |
CLAUDE.md |
Team, every session |
/learn is the team signal. Use it when the rule belongs to the
project, not your personal preferences. Examples:
- ✅ "We always use pnpm in this repo, not npm" →
/learn - ✅ "The conflict-resolver must not push" →
/learn - ❌ "I prefer terse responses" → leave to auto-memory; don't
/learn - ❌ "User pushes back on overengineering" → leave to auto-memory
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.
- 3d ago First seen · 98 lines · 9 tokens per session scan A a4e40d747073
learn is a command published in the GitHub repository sefaertunc/Worclaude (4 stars, last pushed 24d ago), licensed MIT. It adds 9 tokens to every session and 843 once invoked, about $0.0000 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.
Other commands, from other repositories
build
Run full verification pipeline.
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
camera-ready
Convert an accepted anonymous-submission LaTeX paper (AAAI/AIES/ACM-style) to camera-ready and implement the accepted reviews. Use when a paper is accepted with no rebuttal and you need to de-anonymize, add copyright, turn on section numbering, implement each reviewer's minor revisions, optionally move proofs to a…
superpowers-execute
Execute the current GSD phase plan with Superpowers instead of gsd-execute-phase.
generate-rules
Generate development rules and standards into RULES.md.
config
Command "config" from sdebruyn/fabric-dw-mcp-cli, covering configuration & defaults, http retry budget, sql retry budget, mcp workspace allowlist {#mcp-workspace-allowlist} and mcp server log level.