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 skills/dinhanhthi/coding-friend/cf-learnnpx skills add dinhanhthi/coding-friend --skill cf-learngit clone --depth 1 https://github.com/dinhanhthi/coding-friendWrote 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/skills/dinhanhthi/coding-friend/cf-learn)<a href="https://agentmods.dev/skills/dinhanhthi/coding-friend/cf-learn"><img src="https://agentmods.dev/badge/skills/dinhanhthi/coding-friend/cf-learn.svg" alt="Measured on agentmods" 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 | $0.00064 | $0.02332 |
| Opus 5 | $0.00032 | $0.01166 |
| Sonnet 5 | $0.00013 | $0.00466 |
| Haiku 4.5 | $0.00006 | $0.00233 |
Grade A, and why
cf-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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/cf-learn
CLI Requirement: OPTIONAL — Uses the memory MCP from
coding-friend-clifor fast indexed search and storage. Without the CLI: falls back to grep overdocs/memory/and direct file writes. Full functionality preserved, slower memory recall. See CLI requirements.
Extract learning points for human understanding. Topic: $ARGUMENTS
Purpose
In vibe coding, AI writes the code and human approves it — but the human doesn't actually learn anything. This skill extracts knowledge from the conversation and writes it as clear, educational docs so the human builds real understanding over time.
Workflow
Step 0: Custom Guide
Custom guide — auto-loaded below (if the raw command shows instead of its output, run it yourself):
bash "<plugin-root>/lib/load-custom-guide.sh" cf-learn
If output is not empty, integrate returned sections: ## Before → before first step, ## Rules → apply throughout, ## After → after final step.
Step 1: Load Config
Read config from global only:
- Global:
~/.coding-friend/config.json
If learn.disabled is true in the global config, stop immediately and inform the user: "CF Learn is disabled. Re-enable it with cf config or by setting learn.disabled: false in ~/.coding-friend/config.json."
Extract settings with these defaults:
learn settings:
| Setting | Default | Description |
|---|---|---|
learn.language |
en |
Language for cf-learn notes (falls back to top-level language, then en) |
learn.outputDir |
~/.coding-friend/learn |
Where to store learn docs (always global, never project-local) |
learn.categories |
See Step 2 table | Subdirectories and their descriptions |
learn.autoCommit |
false |
Auto git-commit after writing (only if outputDir is a git repo) |
learn.readmeIndex |
false |
Index mode: false (none), true (single README), "per-category" (separate README per category + lightweight main README) |
learn.disabled |
false |
If true, skip all file writing and exit immediately |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 285 lines · 64 tokens per session scan A 5644bacd4647
cf-learn is a skill published in the GitHub repository dinhanhthi/coding-friend (3 stars, last pushed 4d ago), licensed MIT. It adds 64 tokens to every session and 2,332 once invoked, about $0.0003 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 skills, from other repositories
srsa-review
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edu-math-tutorial
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self-improve-with-tinyfish
Enables Hermes to create new reusable skills for itself by researching live web sources with TinyFish Search and Fetch, analyzing source coverage, writing SKILL.md files, and installing them into Hermes memory. Use when the user asks Hermes to learn, teach itself, upgrade itself, or save a reusable capability.
product-help
Use this skill when the user asks about my own features, configuration, or usage — installation, skills, Web UI, CLI, API config, memory, sessions, encryption, white-label, publishing, pricing, troubleshooting, or restarting the server. Do NOT trigger for general coding tasks unrelated to me.
persist-memory
Persist information to long-term memory at /.clacky/memories/. Use when the user asks you to remember/note something, or when reviewing a finished conversation for facts worth keeping. Handles file naming, topic merging, frontmatter, and size limits.
recall-memory
Recall relevant long-term memories on demand. Given a topic or question, judges relevance from pre-loaded metadata, loads only relevant files, and returns a concise summary to the main agent.