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 skills add eugeniosegala/claude-connoisseur --skill learnifygit clone --depth 1 https://github.com/eugeniosegala/claude-connoisseurWrote 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/eugeniosegala/claude-connoisseur/learnify)<a href="https://agentmods.dev/skills/eugeniosegala/claude-connoisseur/learnify"><img src="https://agentmods.dev/badge/skills/eugeniosegala/claude-connoisseur/learnify/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/skills/eugeniosegala/claude-connoisseur/learnify"><img src="https://agentmods.dev/badge/skills/eugeniosegala/claude-connoisseur/learnify.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 | $0.00023 | $0.00788 |
| Opus 5 | $0.00012 | $0.00394 |
| Sonnet 5 | $0.00005 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
learnify 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.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learnify — Isolate Code for Learning
Extract the specified function or code block into a standalone, self-contained script designed for study and hands-on experimentation.
Files and instructions: $ARGUMENTS
Goals
- Produce a single runnable script that works without the original codebase
- Make the code easy to understand, modify, and experiment with
- Allow the reader to study the logic, tweak inputs, and observe outputs in isolation
What the generated script should include
- The target code: the function or code block the user specified, copied verbatim as the starting point
- Inlined dependencies: any helpers, types, constants, or utilities the target code depends on — inlined directly rather than imported, so the script is fully self-contained. Third-party modules (e.g.
lodash,axios,requests,pandas,numpy) should remain as imports — only inline code from the project itself - Comments: add clear, educational comments explaining what the code does, why it works the way it does, and any non-obvious details — treat the reader as someone trying to learn from this code
- Example invocations: concrete calls to the function with realistic sample inputs, covering typical usage and interesting edge cases
- Printed output: log or print the results of each invocation so running the script immediately shows what the code produces
- Editable inputs section: group sample inputs near the top of the script so the reader can easily swap in their own values and re-run
How to interpret arguments
The arguments are free-form and flexible. They may contain:
- File references of any type and in any format:
@file.ts,file.py,main.go, utils.go,script.sh handler.rb - Natural language describing what to isolate, such as:
- "the calculateTax function"
- "the retry logic in the fetch wrapper"
- "the validation pipeline"
- Additional instructions, such as:
- "include the helper functions it calls"
- "add comments explaining the recursion"
- "show edge cases with empty inputs"
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 · 65 lines · 23 tokens per session scan A dae6598ab642
learnify is a skill published in the GitHub repository eugeniosegala/claude-connoisseur (9 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 788 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 skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
miniapp
Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
deck-course-module
A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.
master-yinguang
A reference-based assistant for questions about Yinguang and Pure Land Buddhism, a Buddhist tradition focused on faith, ethical living, and practice connected with rebirth in the Pure Land. It can answer in Yinguang’s historical teaching style.