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 agentmods add agents/argos-ci/docs/ai-ready-docsgit clone --depth 1 https://github.com/argos-ci/docsWhat 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 | $0.00027 | $0.00384 |
| Opus 5 | $0.00014 | $0.00192 |
| Sonnet 5 | $0.00005 | $0.00077 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
ai-ready-docs 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 2d 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
AI-ready docs
This documentation is published with GitBook, which exposes AI-friendly outputs for every page. Point your agent at these endpoints instead of letting it scrape HTML.
Markdown for every page
Append .md to any page URL to get its raw Markdown:
https://argos-ci.com/docs/agents/mcp-server.md
Site indexes: llms.txt and llms-full.txt
https://argos-ci.com/docs/llms.txt— an AI-friendly index of the whole documentation, listing every page with its Markdown URL. Give this to an agent so it can discover and fetch only the pages it needs.https://argos-ci.com/docs/llms-full.txt— a full snapshot of the published documentation in one file, for tools that ingest everything at once.
Docs MCP server
The documentation also exposes its own read-only MCP server, so MCP-compatible tools can search and read these docs directly:
https://argos-ci.com/docs/~gitbook/mcp
For example, with Claude Code:
claude mcp add --transport http argos-docs https://argos-ci.com/docs/~gitbook/mcp
{% hint style="info" %} This docs MCP server answers questions about Argos from the documentation. To let an agent act on your Argos account — list builds, review changes, post comments — connect it to the Argos MCP server instead. {% endhint %}
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.
- 2d ago First seen · 41 lines · 27 tokens per session scan A 0a9726f01b49
ai-ready-docs is an agent published in the GitHub repository argos-ci/docs (5 stars, last pushed 14d ago), licensed MIT. It adds 27 tokens to every session and 384 once invoked, about $0.0001 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 agents, from other repositories
docs
READMEs, API references, architecture notes, changelogs, and inline comments — written for the person who arrives without context.
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Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
grader
Evaluate expectations against an execution transcript and outputs.
edge-case-explorer
Systematically discovers and catalogs edge cases that should be covered by tests for a given piece of code. Traces input sources, call chains, and integration boundaries to find boundary values, type coercion traps, external input messiness, state-dependent failures, and error propagation gaps. Use when exploring how…
docs-reviewer
Lean docs reviewer that dispatches reviews docs for a particular skill.