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 malob/nix-config --skill startgit clone --depth 1 https://github.com/malob/nix-configWrote 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/malob/nix-config/start)<a href="https://agentmods.dev/skills/malob/nix-config/start"><img src="https://agentmods.dev/badge/skills/malob/nix-config/start/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/malob/nix-config/start"><img src="https://agentmods.dev/badge/skills/malob/nix-config/start.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 | $0.00007 | $0.00079 |
| Opus 5.5 | $0.00003 | $0.00032 |
| Sonnet 5.5 | $0.00001 | $0.00016 |
| Haiku 4.5 | $0.00001 | $0.00008 |
Grade A, and why
start scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Enable text-to-speech for this session by creating the session marker file:
touch "${TMPDIR:-/tmp}/tts-enabled-${CLAUDE_SESSION_ID}"
Confirm that TTS is now enabled. Future substantial responses will offer an audio summary.
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 · 14 lines · 7 tokens per session scan A 2bfca4d02cc7
start is a skill published in the GitHub repository malob/nix-config (463 stars, last pushed 6d ago), licensed MIT. It adds 7 tokens to every session and 79 once invoked, about $0.0000 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
restart__pull_request
A pull-request restart workflow for replacing a messy review with a new pull request containing one clean commit and a summary of the earlier discussion.
validate__japanese
A Japanese-language review for Markdown documents, such as READMEs, manuals, and blog drafts. It checks writing style, spacing, line breaks, and links to real code symbols.
prepare__issue
An orchestration workflow that prepares an already acknowledged issue for implementation and changes its status to ready when finished.
rescue__pull_request_review
An automated workflow for handling GitHub pull-request review comments, applying requested code changes, committing them, and pushing them back.
submit__pull_request
An automated pull-request submission workflow. A pull request is a request for a code change to be reviewed and merged; this workflow writes its explanation, creates it, watches its automated checks, and fixes failed checks.
write__structured_comment
A code-commenting rule for recording only knowledge that cannot be expressed in the code, such as unfinished facts, outside-world facts, or explicit user instructions. Each comment must use an approved marker such as TODO or FIXME and stay short.