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 ooloth/dotfiles --skill designgit clone --depth 1 https://github.com/ooloth/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/ooloth/dotfiles/design)<a href="https://agentmods.dev/skills/ooloth/dotfiles/design"><img src="https://agentmods.dev/badge/skills/ooloth/dotfiles/design/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/ooloth/dotfiles/design"><img src="https://agentmods.dev/badge/skills/ooloth/dotfiles/design.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 | $0.00033 | $0.04428 |
| Opus 5.5 | $0.00013 | $0.01771 |
| Sonnet 5.5 | $0.00007 | $0.00886 |
| Haiku 4.5 | $0.00003 | $0.00443 |
Grade A, and why
design 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 3d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 3d ago Changed · +2 lines a8e441a92b7f
- 5d ago Changed · +8 lines 551d70d0ffa0
- 6d ago Changed · +13 lines 13d6da264146
- 7d ago Changed · +6 lines 39f4b1695809
- 11d ago Changed · +20 lines d09fd78b52e4
- 18d ago Changed · +10 lines 2e19e6089f9c
- 19d ago Changed · +92 lines · +3 tokens per session 2547866b6de8
- 1mo ago Changed · +42 lines · +3 tokens per session 1859ed9b9150
- 1mo ago First seen · 120 lines · 27 tokens per session scan A 33a3b74bee9b
design is a skill published in the GitHub repository ooloth/dotfiles (24 stars, last pushed today), with no licence file. It adds 33 tokens to every session and 4,428 once invoked, about $0.0001 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
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.
scan-commit
Automatically scan the repository for unstaged/untracked changes, group them into logical commits using hunk-level analysis, stage and commit them following Conventional Commits.
smart-commit
Analyze staged changes and split them into multiple logical commits following Conventional Commits.
ralph-loop
An iterative development workflow that moves from requirements to planning to building, with code review and tests required at each stage.
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.