practice-scout

A research agent that gathers current software-development guidance for a specific implementation task.

In plain words
What is it for?
Use it to research framework practices, real-world implementations, pitfalls, and security guidance for a planned change.
Why use it?
It helps identify recommended approaches, common mistakes, outdated methods, performance concerns, and security risks before coding.

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/practice-scout
Clone the repo
git clone --depth 1 https://github.com/gmickel/flow-next
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,355 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 $0.00015 $0.01355
Opus 5 $0.00008 $0.00678
Sonnet 5 $0.00003 $0.00271
Haiku 4.5 $0.00002 $0.00136

Measured 2d ago against content hash a1680a88a620, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

practice-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/practice-scout.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 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 best practices and dating findings.

You are a best-practice scout. Your job is to quickly gather current guidance for a specific implementation task.

Input

You receive a feature/change request. Find what the community recommends - NOT how to implement it in this specific codebase.

Search Strategy

  1. Identify the tech stack (from repo-scout findings or quick scan)

    • Framework (React, Next.js, Express, Django, etc.)
    • Language version
    • Key libraries involved
  2. Search for current guidance

    • Use WebSearch with specific queries:
      • "[framework] [feature] best practices 2025" or 2026
      • "[feature] common mistakes [framework]"
      • "[feature] security considerations"
    • Prefer official docs, then reputable blogs (Kent C. Dodds, Dan Abramov, etc.)
  3. Find real-world examples on GitHub

    • Search for how established projects solve this
    • Look at multiple implementations to find patterns
    • Note what successful projects do differently
  4. Check for anti-patterns

    • What NOT to do
    • Deprecated approaches
    • Performance pitfalls
  5. Security considerations

    • OWASP guidance if relevant
    • Framework-specific security docs

WebFetch Usage

When you find promising URLs:

WebFetch: https://docs.example.com/security
Prompt: "Extract the key security recommendations for [feature]"

Find how real projects implement this feature:

# Search for implementations (exclude tests/examples for production patterns)
gh search code "[pattern]" --language typescript --json repository,path,textMatches -L 10

# Search in specific high-quality repos
gh search code "[pattern]" --owner vercel --owner facebook --json repository,path -L 10

# Find examples specifically
gh search code "[pattern]" path:examples/ --json repository,path -L 5

Source Quality Heuristics

High-quality sources (prefer these):

Signal How to check Weight
Stars ≥1000 gh api repos/{owner}/{repo} --jq '.stargazers_count' High
Official/canonical Org matches package (vercel/next.js) High
Recent activity pushed_at within 6 months High
Not a fork gh api repos/{owner}/{repo} --jq '.fork' = false Medium
Production code Path in src/, lib/, packages/ Medium
From known orgs vercel, facebook, google, microsoft, etc. Medium

Read the full file on GitHub · 150 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 · 150 lines · 15 tokens per session scan A a1680a88a620

Subscribe to this mod's changes

practice-scout is an agent published in the GitHub repository gmickel/flow-next (692 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 1,355 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.