Borrowing it
Nothing to install: this file belongs to laurigates/dotfiles. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/laurigates/dotfiles/main/.claude/skills/chezmoi-expert/SKILL.mdgit clone --depth 1 https://github.com/laurigates/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/laurigates/dotfiles/chezmoi-expert)<a href="https://agentmods.dev/skills/laurigates/dotfiles/chezmoi-expert"><img src="https://agentmods.dev/badge/skills/laurigates/dotfiles/chezmoi-expert.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 5.1 | $0.00088 | $0.01475 |
| Opus 5 | $0.00044 | $0.00737 |
| Sonnet 5 | $0.00018 | $0.00295 |
| Haiku 4.5 | $0.00009 | $0.00147 |
Grade A, and why
chezmoi-expert 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 5d 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chezmoi Expert
Expert knowledge for managing dotfiles with chezmoi, including templates, cross-platform support, and best practices.
Core Expertise
- Source vs Target Management: Always work in
~/.local/share/chezmoi/, never edit target files directly - File Naming Conventions:
dot_,private_,readonly_,executable_,exact_,symlink_prefixes - Template System: Go templates with
.chezmoi.*variables for platform-specific configs - Cross-Platform Support: Conditional logic for macOS/Linux differences
Apply workflow
chezmoi apply renders source over target, so it overwrites target-side edits and, inside an exact_ directory, deletes unmanaged entries. Preview before applying:
chezmoi status <tree>— which files are out of sync (M) or would be deleted (D); a path-scoped diff does not show theDlineschezmoi diff <tree>— what would be overwrittenchezmoi apply -v <path>— apply the reviewed path, then let the user review before a fullchezmoi apply
Hazards, --force semantics, and recovery: .claude/rules/chezmoi-apply-hazards.md.
Finding the Source File — Don't Translate Prefixes by Hand
When you know a target path and need the source, ask chezmoi instead
of mentally translating dot_/private_/exact_/.tmpl/encrypted_.
Stacked prefixes make manual guessing error-prone, and a wrong guess points
at a nonexistent path.
chezmoi source-path ~/.zshrc # → .../dot_zshrc.tmpl
chezmoi source-path ~/.config/mise/config.toml # → .../private_dot_config/mise/config.toml.tmpl
chezmoi target-path <source-file> # inverse: source → target
Canonical edit loop: chezmoi source-path <target> → Read it → Edit
it → chezmoi apply. source-path exits non-zero when the target is not
managed — check the exit code; if it errors, use chezmoi unmanaged <path>
or chezmoi managed <path> to confirm whether the file is unmanaged vs.
ignored (chezmoi ignored).
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.
- 5d ago Changed · +4 lines 8b66c41becb4
- 8d ago First seen · 149 lines · 88 tokens per session scan A b6b4ecb1c8aa
chezmoi-expert is a skill published in the GitHub repository laurigates/dotfiles (10 stars, last pushed 4d ago), licensed MIT. It adds 88 tokens to every session and 1,475 once invoked, about $0.0004 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
dotfiles-bootstrap
Bootstrap a workstation with the dotfiles framework. Takes a GitHub user / owner+repo / explicit clone URL and runs dot init (which shells out to chezmoi) with the right safety prompts. Honors the active agent profile (ask / plan / apply / audit) so it defaults to dry-run in safer modes and full apply in apply.
vibe
Delegate a coding task to a cheap AI model (Mistral Vibe by default, but any provider Vibe knows about — DeepSeek, Gemini Flash, etc.) and supervise the result via git diff. Claude orchestrates, the cheap model codes. Claude consumes 500-1500 tokens per delegation regardless of how many file reads the delegate does…
work-on
End-to-end workflow for shipping a GitHub issue. Assesses complexity, builds a tailored workflow, and orchestrates skills from research through PR.
gather-context
Build comprehensive understanding of a problem by gathering context from GitHub issues, codebase exploration, git history, and linked references. Use when starting work on an issue or investigating a problem.
plan
Design an implementation as a task graph with explicit dependencies, parallel phases, and agent team topology. Use after gathering context and agreeing on an approach, when the work is large enough that sequencing it badly costs real time.
youtube
Fetch and structure the transcript from this YouTube video.