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.
git clone --depth 1 https://github.com/ofershap/flutter-best-practicesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/ofershap/flutter-best-practices/audit)<a href="https://agentmods.dev/commands/ofershap/flutter-best-practices/audit"><img src="https://agentmods.dev/badge/commands/ofershap/flutter-best-practices/audit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/ofershap/flutter-best-practices/audit"><img src="https://agentmods.dev/badge/commands/ofershap/flutter-best-practices/audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00012 | $0.00195 |
| Opus 5.5 | $0.00005 | $0.00078 |
| Sonnet 5.5 | $0.00002 | $0.00039 |
| Haiku 4.5 | $0.00001 | $0.00019 |
Grade A, and why
audit 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 1mo 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.
What it actually says
Scan the current project for Flutter anti-patterns and best practice violations.
Check for:
- Navigator 1.0 (push/pop) instead of GoRouter
- Pre-Dart 3 patterns (if/else chains vs sealed classes, Map vs records)
- StatefulWidget with setState for shared state instead of Riverpod
- Missing const constructors where applicable
- Hardcoded colors/sizes instead of Theme.of(context)
- Nested scrollable widgets (ListView in Column)
- Raw String/int IDs instead of extension types
- Using dynamic instead of proper types
- Context used after async gap (mounted check)
For each issue found:
- Show the file and line
- Explain what's wrong
- Show the correct pattern
- Rate severity: critical / warning / info
Use the flutter-best-practices skill for reference on current best practices.
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.
- 1mo ago First seen · 28 lines · 12 tokens per session scan A ddc8ebf1fcb2
audit is a command published in the GitHub repository ofershap/flutter-best-practices (1 stars, last pushed 7mo ago), licensed MIT. It adds 12 tokens to every session and 195 once invoked, about $0.0000 per session on Opus 5.5. 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 commands, from other repositories
audit
Audit the current codebase for Expo / React Native best practice violations.
codebase-review
Review an entire codebase for architecture, engineering health, and exploitable risk; generate a prioritized remediation plan, an evidence-anchored system knowledge document, or both.
review-ticket
Review a ticket or PR through focused specialist lenses: scope, architecture, security, tests, AC coverage, and PR metadata.
code-review
Run an AI-assisted PR code review using multi-layer lenses with confidence scoring.
is-not-duplicated
please investigate the codebase based on your changes - do we have code duplication? After analysis, write updates to DUPLICATIONREPORT.md with the results. Keep in mind that other agents could keep their records, so you need to check the document first, decided to update or add new information.
inconsistences
TODOs, errors, incosistencies, potential code and typesafety violations in.