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 GeonheeYe/multi-agent-dotfiles --skill applygit clone --depth 1 https://github.com/GeonheeYe/multi-agent-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/geonheeye/multi-agent-dotfiles/apply)<a href="https://agentmods.dev/skills/geonheeye/multi-agent-dotfiles/apply"><img src="https://agentmods.dev/badge/skills/geonheeye/multi-agent-dotfiles/apply/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/geonheeye/multi-agent-dotfiles/apply"><img src="https://agentmods.dev/badge/skills/geonheeye/multi-agent-dotfiles/apply.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 | $0.00047 | $0.02477 |
| Opus 5.5 | $0.00019 | $0.00991 |
| Sonnet 5.5 | $0.00009 | $0.00495 |
| Haiku 4.5 | $0.00005 | $0.00248 |
Grade A, and why
apply 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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 · 169 lines · 47 tokens per session scan A 59c1406e822d
apply is a skill published in the GitHub repository GeonheeYe/multi-agent-dotfiles (3 stars, last pushed 13d ago), with no licence file. It adds 47 tokens to every session and 2,477 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 2026-08-31.
Other skills, from other repositories
browser-use
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers hosted cloud browsers for AI agents: the browser-use Python library (Browser(usecloud=True)), Playwright, Puppeteer or any CDP client.
computer-use
Choose Memmy browser, desktop Computer Use, or a structured connector for a live task on macOS or Windows 11; keep Computer History retrieval separate from UI actions.
Agent Browser Automation
Fast Rust-based headless browser automation CLI with Node.js fallback for AI agents, featuring navigation, clicking, typing, snapshots, and structured commands optimized for agent workflows.
audit-accomplishments
Use when preparing a performance self-reflection, midyear or annual review, promotion packet, or brag document; when asked to collect, mine, gather, or summarize your accomplishments, contributions, or impact over a period; or when assembling cited evidence of work done across GitHub, Jira, Notion, Slack, and local…
start-day
Use at the start of a workday or when the user says "start my day", "good morning", "/start-day", "morning", "what should I work on today", or wants a catch-up on what happened while they were away. Use when the user wants a short ranked list of what to tackle today.
webapp-testing
Browser-tests a local webapp end to end — starts the app, installs Playwright if missing, writes a spec for the critical path plus edge cases, runs headless, captures screenshots, console and network logs on failure, and reports a pass/fail table with repro steps. Degrades to curl smoke tests when no browser is…