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/0xmh/claude-skillify/skillifynpx skills add 0xMH/claude-skillify --skill skillifygit clone --depth 1 https://github.com/0xMH/claude-skillifyWrote 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/0xmh/claude-skillify/skillify)<a href="https://agentmods.dev/skills/0xmh/claude-skillify/skillify"><img src="https://agentmods.dev/badge/skills/0xmh/claude-skillify/skillify.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 | $0.00026 | $0.01792 |
| Opus 5 | $0.00013 | $0.00896 |
| Sonnet 5 | $0.00005 | $0.00358 |
| Haiku 4.5 | $0.00003 | $0.00179 |
Grade A, and why
skillify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to skillify — 31 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skillify
You are capturing this session's repeatable process as a reusable skill.
Your Session Context
You have the full conversation history available to you. Analyze it directly to understand what process was performed, what tools were used, and how the user steered you.
If a description was provided: The user described this process as: "$description"
Your Task
Step 1: Analyze the Session
Before asking any questions, analyze the conversation history to identify:
- What repeatable process was performed
- What the inputs/parameters were
- The distinct steps (in order)
- The success artifacts/criteria (e.g. not just "writing code," but "an open PR with CI fully passing") for each step
- Where the user corrected or steered you
- What tools and permissions were needed
- What agents were used
- What the goals and success artifacts were
Step 2: Interview the User
You will use AskUserQuestion to understand what the user wants to automate. Important notes:
- Use AskUserQuestion for ALL questions! Never ask questions via plain text.
- For each round, iterate as much as needed until the user is happy.
- The user always has a freeform "Other" option to type edits or feedback -- do NOT add your own "Needs tweaking" or "I'll provide edits" option. Just offer the substantive choices.
Round 1: High level confirmation
- Suggest a name and description for the skill based on your analysis. Ask the user to confirm or rename.
- Suggest high-level goal(s) and specific success criteria for the skill.
Round 2: More details
- Present the high-level steps you identified as a numbered list. Tell the user you will dig into the detail in the next round.
- If you think the skill will require arguments, suggest arguments based on what you observed. Make sure you understand what someone would need to provide.
- If it's not clear, ask if this skill should run inline (in the current conversation) or forked (as a sub-agent with its own context). Forked is better for self-contained tasks that don't need mid-process user input; inline is better when the user wants to steer mid-process.
- Ask where the skill should be saved. Suggest a default based on context (repo-specific workflows -> repo, cross-repo personal workflows -> user). Options:
- This repo (
.claude/skills/<name>/SKILL.md) -- for workflows specific to this project - Personal (
~/.claude/skills/<name>/SKILL.md) -- follows you across all repos
- This repo (
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.
- 4d ago First seen · 148 lines · 26 tokens per session scan A 5c3ad4edac16
skillify is a skill published in the GitHub repository 0xMH/claude-skillify (45 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 1,792 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to skillify, differing in 31 lines, and is treated as a copy.
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