agent-ready

A command that organizes a repository's documentation so AI tools can read it more reliably. It creates or repairs llms.txt, a map of the documentation, adds document details, and records writing conventions.

In plain words
What is it for?
Use it to prepare an existing documentation folder for coding agents, documentation assistants, and search systems.
Why use it?
AI tools work better when they can first see where documents are and how they are structured. This reduces confusion caused by missing metadata or inconsistent project rules.

Command

Install

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.

agentmods
npx agentmods add commands/edwardangert/docs-agent-plugin/agent-ready
Clone the repo
git clone --depth 1 https://github.com/EdwardAngert/docs-agent-plugin
Per session 27 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 799 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00027 $0.00799
Opus 5 $0.00014 $0.00400
Sonnet 5 $0.00005 $0.00160
Haiku 4.5 $0.00003 $0.00080

Measured yesterday against content hash 865b1b497933, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-ready 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 yesterday.

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.

commands/agent-ready.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Make the Docs Agent-Ready

Make this repository's documentation legible to AI tools: coding agents, docs assistants, and search systems that read structure before prose.

Readers are no longer only human. An agent answering questions about this project will do it well or badly depending on whether the docs have a map (llms.txt), per-doc metadata (frontmatter), and consistent conventions it can rely on. This command retrofits all three onto an existing docs set. The optional argument ($ARGUMENTS) is the docs directory. Detect it if not given.

Process

1. Survey the Docs Set

  • Resolve .docs-assist/ config if present.
  • Inventory the docs: paths, titles, and what frontmatter each already carries.
  • Learn the repo's frontmatter field names and any SSG-required fields, per ${CLAUDE_PLUGIN_ROOT}/skills/docs-assist/reference/frontmatter-spec.md. The repo's conventions win; never fight the build system.

2. Create or Repair llms.txt

llms.txt is the map an AI tool reads first. The format, ordering, and maintenance contract are single-sourced in ${CLAUDE_PLUGIN_ROOT}/skills/docs-assist/reference/llms-txt.md; follow it exactly.

  • Missing: generate one to that spec: the H1 project name, the blockquote summary, then sections of - [title](path): description entries in reader-priority order.
  • Present: reconcile it against the docs. Add missing entries, remove entries whose files are gone, fix titles, descriptions, and paths that drifted, and restore reader-priority order where it decayed.
  • Reserve a section named Optional for genuinely skippable depth (the convention gives that name meaning to AI readers); use descriptive names for everything else.
  • For a small set, offer the llms-full.txt companion per the reference.

3. Complete the Frontmatter

For each doc missing required metadata, add it using the repo's field names:

  • title, description, and the content-type field at minimum; audience and keywords where the content makes them clear.
  • Never overwrite an existing field, and never remove or reorder SSG-required fields.
  • Derive values from the doc's own content. Where a doc is too ambiguous to describe honestly, flag it for its owner instead of inventing a description.

Read the full file on GitHub · 56 lines

Changes

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.

  1. yesterday First seen · 56 lines · 27 tokens per session scan A 865b1b497933

Subscribe to this mod's changes

agent-ready is a command published in the GitHub repository EdwardAngert/docs-agent-plugin (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 27 tokens to every session and 799 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.