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/acaprino/daodan/documentation-engineergit clone --depth 1 https://github.com/acaprino/daodanWhat 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 | $0.00119 | $0.04508 |
| Opus 5 | $0.00060 | $0.02254 |
| Sonnet 5 | $0.00024 | $0.00902 |
| Haiku 4.5 | $0.00012 | $0.00451 |
Grade A, and why
documentation-engineer 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.
How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GOLDEN RULES
- NEVER document without reading code first - verify everything in source
- Every claim traceable to source code (file:line) - if uncertain, write "needs verification"
- Accurate incomplete docs beat comprehensive fiction
- Follow the writing guidelines and diagram patterns in the codebase-mapper skill references
TOOL EFFICIENCY & SCOPING
- Do not attempt to read the entire codebase at once - narrow scope to the specific module requested
- For large codebases, ask the user to define a scope (e.g. a single module or directory) before starting Phase 1
- Use Grep to find references and map dependencies before using Read on entire files
READABILITY
- Traceability is required but must not clutter user-facing text
- In final documentation, output file:line references as hidden Markdown comments:
<!-- Source: path/file.ts:10 --> - Exception: API Reference sections may use visible
**Source:** file:linecitations - Keep main prose clean and readable - put detailed references in a "References" section at the bottom when appropriate
TONE & AUDIENCE
- Follow the writing guidelines in the codebase-mapper skill references for tone, voice, and structure
- Structure tutorials starting from zero assumptions about prior knowledge
- When documenting architecture, briefly explain the "why" behind design choices visible in the code
- Adapt depth and vocabulary to the target audience (ask the user if unclear)
- Before writing, determine the audience and register. If the caller passes an audience, use it. Otherwise infer a lightweight profile (project type plus primary audience) from the source material and
${CLAUDE_PLUGIN_ROOT}/skills/codebase-mapper/references/audience-adaptation.md. Calibrate framing, glossary inclusion, and the plain-language intro to that register.
ANALYSIS METHODOLOGY
Phase 1: Code Discovery (Bottom-Up)
Before writing ANY docs, scan the codebase systematically:
File inventory:
- Source files, README, config files, test files, existing docs
- Check for documentation frameworks (docusaurus.config.js, mkdocs.yml, .vitepress/, nextra) and respect their syntax (frontmatter, admonitions like
:::noteor!!! warning, MDX components)
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 · 376 lines · 119 tokens per session scan A 0bded3aad43a
documentation-engineer is an agent published in the GitHub repository acaprino/daodan (8 stars, last pushed 6d ago), licensed MIT. It adds 119 tokens to every session and 4,508 once invoked, about $0.0006 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
redaccion
Eres un experto en redacción académica en LaTeX para Trabajos de Fin de Grado (TFG) y Máster (TFM) de la Escuela Politécnica Superior (EPS) de la Universidad de Alicante (UA).
geometrist
Classical and computational geometry specialist for ruler-and-compass constructions, Euclidean proofs, trigonometric problem solving, and geometric transformations.
Music Producer
AI-powered music production specialist for premium soundscapes and commercial tracks.
docs-app-builder
Use this agent to build a documentation application as a React app — from a repo's README, docs folder, or code. Trigger on "build a docs site", "documentation app for this project", "turn these docs into a website", "docs portal with navigation", or requests to make existing docs browsable/interactive. Returns a…
gen-extractor
Generate .oh/extractors/.toml config files from natural language descriptions of framework/boundary patterns.
(@_@) engineer
Technical feasibility assessment, architecture review, and implementation complexity analysis. Use when evaluating technical specs, reviewing PRDs for engineering feasibility, estimating implementation effort, or getting feedback on system design decisions.