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 urmzd/dotfiles --skill sync-ecosystem-to-chezmoigit clone --depth 1 https://github.com/urmzd/dotfilesWrote 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/urmzd/dotfiles/sync-ecosystem-to-chezmoi)<a href="https://agentmods.dev/skills/urmzd/dotfiles/sync-ecosystem-to-chezmoi"><img src="https://agentmods.dev/badge/skills/urmzd/dotfiles/sync-ecosystem-to-chezmoi/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/urmzd/dotfiles/sync-ecosystem-to-chezmoi"><img src="https://agentmods.dev/badge/skills/urmzd/dotfiles/sync-ecosystem-to-chezmoi.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 | $0.00114 | $0.00973 |
| Opus 5 | $0.00057 | $0.00487 |
| Sonnet 5 | $0.00023 | $0.00195 |
| Haiku 4.5 | $0.00011 | $0.00097 |
Grade A, and why
sync-ecosystem-to-chezmoi 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 9d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sync Ecosystem to Chezmoi
This is the chezmoi-specific tail of the sync-ecosystem workflow. The base skill audits a repo against ecosystem conventions and emits a drift report. This skill takes that report and applies it to the chezmoi-managed canonical skill source, then redeploys.
When to Use
- You ran
sync-ecosystem <repo>and have a drift report to apply. - You maintain your agent skills in a chezmoi source tree and need the deployed copies under
${CLAUDE_SKILL_DIR:-$HOME/.agents/skills}/to follow. - A new or stale skill needs to be promoted from a project repo into the canonical store.
If you don't use chezmoi, stop here. The portable audit lives in sync-ecosystem; you can substitute your own deploy step.
Prerequisites
chezmoi --version # CLI present
chezmoi source-path # confirm the source dir, typically ~/.local/share/chezmoi
The canonical skill source lives under <chezmoi-source>/dot_agents/skills/. Deployed copies under ${CLAUDE_SKILL_DIR:-$HOME/.agents/skills}/ are overwritten on every chezmoi apply, so never edit them directly.
Workflow
-
Receive the drift report. Typically produced by running
sync-ecosystem <repo-path>first. The report lists missing artifacts, content drift, and canonical-store coverage issues per skill. -
For each finding, decide the target file.
Finding type Target Skill in repo but not in canonical store New dir under <chezmoi-source>/dot_agents/skills/<name>/Stale canonical skill (frontmatter / body drift) Existing <chezmoi-source>/dot_agents/skills/<name>/SKILL.mdAsset / script drift inside a skill Matching file under that skill's assets/orscripts/Required ecosystem doc missing Owner skill in the chezmoi source (e.g. community-health/assets/) -
Apply edits in the source, never in
~/.agents/skills/. UseEdit/Writeagainst the chezmoi source paths. Preserve frontmatter formatting and the rest of the file.
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.
- 9d ago First seen · 73 lines · 114 tokens per session scan A 9eda0c182bcc
sync-ecosystem-to-chezmoi is a skill published in the GitHub repository urmzd/dotfiles (3 stars, last pushed 3d ago), licensed Apache-2.0. It adds 114 tokens to every session and 973 once invoked, about $0.0006 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
benchling-integration
Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.
mcp-notion-usage-guide
A usage guide for connecting AI agents to Notion databases through MCP. Notion is a workspace for documents and databases, while a database view is a saved way of displaying database records.
astropy
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
esm
Comprehensive toolkit for EvolutionaryScale protein language models including ESM3 (generative multimodal design across sequence, structure, and function) and ESM C (efficient embeddings). Use for protein sequence/structure/function tasks, inverse folding, embeddings, variant design, and ESMFold2 structure prediction…
ralph-loop
An iterative development workflow that moves from requirements to planning to building, with code review and tests required at each stage.
create-pr
Rebase from the latest origin/main, squash the commits from it, and then create a PR on github with intelligent commit messages based on staged changes.