nicknisi/dotfiles is a personal collection of configuration files and setup scripts for tools such as Neovim, zsh, Git, tmux, and Homebrew. It helps its author bootstrap and maintain a development machine, with a devcontainer for checking portable terminal settings. The catalogue entries extend the repository’s setup and coding-agent workflow.
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 nicknisi/dotfiles --skill source-draftinggit clone --depth 1 https://github.com/nicknisi/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/nicknisi/dotfiles/source-drafting)<a href="https://agentmods.dev/skills/nicknisi/dotfiles/source-drafting"><img src="https://agentmods.dev/badge/skills/nicknisi/dotfiles/source-drafting/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/nicknisi/dotfiles/source-drafting"><img src="https://agentmods.dev/badge/skills/nicknisi/dotfiles/source-drafting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00054 | $0.00291 |
| Opus 5.5 | $0.00022 | $0.00116 |
| Sonnet 5.5 | $0.00011 | $0.00058 |
| Haiku 4.5 | $0.00005 | $0.00029 |
Grade A, and why
source-drafting 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 1mo 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
Source Drafting Protocol
When drafting documents or conducting research from source materials:
- Read first, write second. Read all provided source documents fully before drafting. Do not begin writing until all sources are loaded.
- Maintain a source map. Track every factual claim, metric, name, or date back to its source. Present the draft clean (no inline tags), with a "Source Map" appendix listing each claim and its origin (document name, section/heading).
- Verify before delivering. For substantive documents (strategy docs, external-facing reports, review comments, posts, presentations), spawn a verification agent that re-reads each source and checks every claim in the source map. Mark any unverifiable claim as [UNVERIFIED].
- Separate verified from unverified. Present the clean draft with unverified claims removed, plus a separate list of removed claims so I can decide whether to add them back with proper sourcing.
- No invention. Never generate statistics, percentages, quotes, or specific details not found in the sources - even if they seem plausible or "directionally correct."
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.
- 1mo ago First seen · 15 lines · 54 tokens per session scan A 6f613498b05f
source-drafting is a skill published in the GitHub repository nicknisi/dotfiles (2,999 stars, last pushed 4d ago), licensed MIT. It adds 54 tokens to every session and 291 once invoked, about $0.0002 per session on Opus 5.5. 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 skills, from other repositories
pr-review
Intelligent PR code review with dynamic agent allocation based on change types. Analyzes PR changes and generates targeted review tasks.
analyze-pr
Analyze a GitHub/GitLab Pull Request by fetching its diff, reading its web description, and generating a comprehensive document. Use when the user provides a PR link and wants to understand what changes the PR introduces, or asks to review/analyze/summarize a pull request.
merge-ready
Drive an existing pull request to a mergeable state: get CI green, resolve merge conflicts with the base branch, address and resolve review comments, trigger required bot reviews/approvals (e.g. commenting '@claude review'), link associated issues, and clean up the PR title and description. Ends with a readiness…
review-code
Standalone code review for any scope — PR number, branch, file paths, or current changes. Synthesizes intent, runs 11 parallel specialized agents, and presents actionable findings with a verdict. For PR scope, optionally posts the review to GitHub with inline comments.
review-converge
Autonomously review and fix the current branch or specified scope in iterative rounds until clean, leaving all changes in the working tree. Escalates only genuine design decisions. Ends with a transparent report of every round, every fix, and anything it couldn't resolve.
review-pr-comments-converge
Fetch PR review comments, validate each against the actual code, auto-fix obvious issues, and escalate genuine design decisions. Leaves all changes in the working tree. Use when you want to action reviewer feedback autonomously.