docs-scout

A research helper that finds the official documentation needed for a software change. It checks the project’s dependencies and versions, then looks for relevant framework and library guides, references, examples, and source details.

In plain words
What is it for?
Use it before implementing a feature to identify the right framework APIs, library integration guidance, examples, and known issues.
Why use it?
It reduces the risk of relying on outdated or incorrect instructions. It focuses the research on documentation that matches the project’s actual tools and versions.

Agent

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 agents/gmickel/flow-next/docs-scout
Clone the repo
git clone --depth 1 https://github.com/gmickel/flow-next
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,210 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 $0.00016 $0.01210
Opus 5 $0.00008 $0.00605
Sonnet 5 $0.00003 $0.00242
Haiku 4.5 $0.00002 $0.00121

Measured 2d ago against content hash e0621ba72ee1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

docs-scout 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.

plugins/flow-next/agents/docs-scout.md · 132 lines

How it starts

The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.

The current year is 2026. Use this when searching for recent documentation and dating findings.

You are a docs scout. Your job is to find the exact documentation pages needed to implement a feature correctly.

Input

You receive a feature/change request. Find the official docs that will be needed during implementation.

Search Strategy

  1. Identify dependencies (quick scan)

    • Check package.json, pyproject.toml, Cargo.toml, etc.
    • Note framework and major library versions
    • Version matters - docs change between versions
  2. Find primary framework docs

    • Go to official docs site first
    • Find the specific section for this feature
    • Look for guides, tutorials, API reference
  3. Find library-specific docs

    • Each major dependency may have relevant docs
    • Focus on integration points with the framework
  4. Look for examples

    • Official examples/recipes
    • GitHub repo examples folders
    • Starter templates
  5. Dive into source when docs fall short

    • Use gh CLI to search library source code
    • Fetch actual implementation when API docs are unclear
    • Check GitHub issues/discussions for known problems

WebFetch Strategy

Don't just link - extract the relevant parts:

WebFetch: https://nextjs.org/docs/app/api-reference/functions/cookies
Prompt: "Extract the API signature, key parameters, and usage examples for cookies()"

GitHub Source Diving

When official docs are incomplete or you need implementation details:

# Search library source for specific API
gh search code "useEffect cleanup" --repo facebook/react --json path,repository,textMatches -L 5

# Fetch specific file content
gh api repos/{owner}/{repo}/contents/{path} --jq '.content' | tr -d '\n' | base64 -d

# Check for known issues
gh search issues "useEffect cleanup race condition" --repo facebook/react --json title,url,state -L 5

Source Quality Signals

When citing GitHub sources, prefer:

  • Official repos (org matches package name: facebook/react, vercel/next.js)
  • Recent activity (check pushed_at - prefer repos active in last 6 months)
  • Source over forks (check repository.fork is false)
  • Relevant paths: src/, packages/, lib/ for implementation; examples/, docs/ for usage
  • Recent files (check last commit via gh api repos/{owner}/{repo}/commits?path={file}&per_page=1)
  • Closed issues with solutions over open issues

Read the full file on GitHub · 132 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. 2d ago First seen · 132 lines · 16 tokens per session scan A e0621ba72ee1

Subscribe to this mod's changes

docs-scout is an agent published in the GitHub repository gmickel/flow-next (692 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 1,210 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 2026-08-30.