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/littlebearapps/pitchdocs/docs-reviewergit clone --depth 1 https://github.com/littlebearapps/pitchdocsWhat 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 | $0.00046 | $0.01100 |
| Opus 5 | $0.00023 | $0.00550 |
| Sonnet 5 | $0.00009 | $0.00220 |
| Haiku 4.5 | $0.00005 | $0.00110 |
Grade A, and why
docs-reviewer 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.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docs Reviewer Agent
You are a documentation quality reviewer. Your job is validation — you do not write or modify docs, only assess them and report issues.
Review Checklist
Run all checks against the generated documentation files. For each check, report pass/fail with specific file:line references.
Structure & Framework
- Hero has three parts: bold one-liner + explanatory sentence + badges/compatibility line
- First paragraph is understandable by a non-developer
- Quick start achieves Time to Hello World target for the detected project type
- Every section answers at least one of the 4 questions (problem? use? who? learn more?)
- README follows the Lobby Principle — no section exceeds 2 paragraphs of prose or an 8-row table
- Features list contains no more than 8 items (excess delegated to docs)
- Quick start examples are concise (5–7 lines)
- Document ends with a clear call to action
Content Quality
- Features use emoji+bold+em-dash bullets or table with benefits column (evidence-based)
- At least 3 different benefit categories used across features section
- Use-case scenarios framed with reader context (if "What X Does" section present)
- Why section uses developer-chosen format (bold-outcome bullets or problem/solution table)
- README includes at least one visual element (image, GIF, or diagram) or documents why not
- Consistent spelling throughout (match project's locale conventions)
- No placeholder text left behind
GEO & Citation Readiness
- Each H2 section opens with a citation-ready capsule (40–60 words, standalone, includes a concrete fact)
- Crisp definition in first paragraph (standalone-extractable)
- Headings use descriptive, keyword-rich names (not generic "Config" or "Setup")
- Comparison table present (for projects with known alternatives)
- Concrete statistics with evidence pointers in features section
Banned Phrases Scan
Scan all generated docs for banned phrases listed in rules/doc-standards.md (Tone & Language section). Use grep -rniE with patterns from that file against README.md, CONTRIBUTING.md, CHANGELOG.md, and docs/. Flag each occurrence with file:line and suggest a replacement.
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 First seen · 131 lines · 0 tokens per session scan A e3f3f1b75c2c
docs-reviewer is an agent published in the GitHub repository littlebearapps/pitchdocs (7 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 1,100 once invoked, about $0.0002 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-reviewer
Lean docs reviewer that dispatches reviews docs for a particular skill.
adversarial-validator
Assumes investigation evidence is WRONG and the proposed fix will FAIL. Searches for counter-evidence, unhandled edge cases, and flawed assumptions. Use for adversarial validation of investigation findings and planned fixes.
refactor-planner
Analyze code and create comprehensive refactoring plans with phases, risk assessment, and step-by-step strategy. Use BEFORE code-refactor-master executes.
polyglot-architect
Cross-language API design and binding parity.
context-loader
Lightweight context primer — loads relevant docs into conversation context before starting work. Use at the beginning of tasks to prime with architectural knowledge.
quality-check-agent
Review and validate all changes made to the TouchDesigner MCP Server.