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/pleaseai/claude-code-plugins/generate-skillgit clone --depth 1 https://github.com/pleaseai/claude-code-pluginsWhat 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 | $0.00035 | $0.00566 |
| Opus 5 | $0.00017 | $0.00283 |
| Sonnet 5 | $0.00007 | $0.00113 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
generate-skill 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 2d 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
Generate agent skills for the project: $ARGUMENTS
Follow the guidelines in docs/skills-generator.md to generate Type 1 skills.
Steps
- Read
docs/skills-generator.mdfor the full generation guidelines - Check
vendor/antfu-skills/instructions/$ARGUMENTS.mdfor project-specific instructions (if it exists) - Read source docs from
sources/$ARGUMENTS/docs/ - Generate skill files into
skills/$ARGUMENTS/:SKILL.md— index with frontmatter (name,description,metadata) and a table of all referencesGENERATION.md— tracking metadata (source path, git SHA, generation date)references/*.md— one file per concept (prefixed by category, e.g.core-syntax.md,features-plugins.md)
- Copy the generated skills into the plugin directory:
mkdir -p "plugins/$ARGUMENTS/skills/$ARGUMENTS/" && cp -r "skills/$ARGUMENTS/." "plugins/$ARGUMENTS/skills/$ARGUMENTS/"Note:
bun run skills:synconly handles Type 2 (vendor) and Type 3 (manual) skills. Type 1 (generated) skills must be copied manually to the plugin directory. - Commit the generated skills:
git add skills/$ARGUMENTS/ plugins/$ARGUMENTS/skills/$ARGUMENTS/ git commit -m "feat($ARGUMENTS): generate skills from official documentation"
Output Location
- Source docs:
sources/$ARGUMENTS/(submodule, runbun scripts/cli.ts initif missing) - Generated skills:
skills/$ARGUMENTS/(our own skills directory, never modifyvendor/antfu-skills/) - Synced to plugin:
plugins/$ARGUMENTS/skills/$ARGUMENTS/
Writing Guidelines
- Rewrite docs for agents — synthesize, don't copy verbatim
- Focus on practical usage patterns and code examples
- Omit installation guides, introductions, and content agents already know well
- One concept per reference file
- Include working code examples
- Explain when and why to use each feature, not just how
- Keep each reference file concise (under 200 lines)
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.
- 2d ago First seen · 45 lines · 35 tokens per session scan A 8a68b1ba67cb
generate-skill is a command published in the GitHub repository pleaseai/claude-code-plugins (13 stars, last pushed 7d ago), licensed MIT. It adds 35 tokens to every session and 566 once invoked, about $0.0002 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.