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.
git clone --depth 1 https://github.com/Cristhianzl/claude-skills-czlWrote 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/commands/cristhianzl/claude-skills-czl/learn)<a href="https://agentmods.dev/commands/cristhianzl/claude-skills-czl/learn"><img src="https://agentmods.dev/badge/commands/cristhianzl/claude-skills-czl/learn/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/commands/cristhianzl/claude-skills-czl/learn"><img src="https://agentmods.dev/badge/commands/cristhianzl/claude-skills-czl/learn.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 | $0.00026 | $0.00349 |
| Opus 5 | $0.00013 | $0.00175 |
| Sonnet 5 | $0.00005 | $0.00070 |
| Haiku 4.5 | $0.00003 | $0.00035 |
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 12d 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.
What it actually says
Capture a durable learning from what just happened — but only if it's worth keeping, and place it where it belongs. This upgrades the plain "append a learning" step with a quality gate so learnings/ doesn't fill with duplicates.
-
Identify the single most reusable insight from this session — a convention, constraint, trap, or fix pattern. Skip trivial or one-off fixes.
-
Check for overlap first (don't append blindly):
- Grep the relevant skill's
learnings/and any projectlearnings//MEMORY.mdfor the same topic and keywords. - Consider whether appending to an existing learning would suffice.
- Grep the relevant skill's
-
State a verdict, then act:
- Save — unique and reusable → write
skills/<skill>/learnings/YYYY-MM-DD-slug.md(frontmatterdescription:; body = the rule + Why + How to apply). - Improve then Save — tighten the scope/wording, then save.
- Absorb into [X] — append to the existing learning instead; show the diff.
- Drop — trivial or already covered → say so and stop.
- Save — unique and reusable → write
-
Put it in the most specific skill it belongs to (a DB trap →
developing-features/learnings/; a review heuristic →reviewing-code/learnings/). One pattern per file; body ≤ ~30 lines.
Confirm with the user before writing the file. Never run git.
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.
- 12d ago First seen · 22 lines · 26 tokens per session scan A caf0520bfc24
learn is a command published in the GitHub repository Cristhianzl/claude-skills-czl (5 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 349 once invoked, about $0.0001 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
explain-code
Walk through a file, function, class, or module and explain what it does, how it works, and why it is structured the way it is. Suited for onboarding onto unfamiliar code, understanding a complex algorithm, or preparing to modify something you have not read before. Pass a file path or a symbol name as the argument.…
ars-revision-coach
ARS academic-paper revision-coach mode — Revision Roadmap + Response Letter Skeleton.
color-palette
Generate an accessible colour palette from a hex value.
ux-extract
Exhaustively extract UX patterns from a reference web app into a reusable pattern library.
diagram-from-url
Generate educational diagram from a URL source using Excalidraw.
evaluate
Execute Evaluate stage to validate generated framework artifacts.