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 commands/ofershap/expo-best-practices/auditgit clone --depth 1 https://github.com/ofershap/expo-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/expo-best-practices/audit)<a href="https://agentmods.dev/commands/ofershap/expo-best-practices/audit"><img src="https://agentmods.dev/badge/commands/ofershap/expo-best-practices/audit.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.00091 |
| Opus 5 | $0.00008 | $0.00046 |
| Sonnet 5 | $0.00003 | $0.00018 |
| Haiku 4.5 | $0.00002 | $0.00009 |
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 5d 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.
This is a copy
81% identical to audit — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Scan the current project for Expo / React Native anti-patterns and best practice violations.
For each issue found:
- Show the file and line
- Explain what's wrong
- Show the correct pattern
- Rate severity: critical / warning / info
Use the expo-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.
- 5d ago First seen · 16 lines · 15 tokens per session scan A 3e964a64190a
audit is a command published in the GitHub repository ofershap/expo-best-practices (1 stars, last pushed 6mo ago), licensed MIT. It adds 15 tokens to every session and 91 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to audit, differing in 6 lines, and is treated as a copy.
Other commands, from other repositories
audit
Audit the current codebase for Flutter best practice violations.
review-code
Read ALL memory bank code rules + best practices, check the files that changed, and APPLY fixes so they adhere. The active counterpart to /scan (which is read-only). Use after an AI session, before commit, to make changed files compliant.
init
Command "init" from chohra-med/expo_boilerplate, covering command: init — spec-driven bootstrap, invocation, step 1 — capture intent (the interview, one message), step 2 — scaffold (copy from templates/, fill the {{...}}) and step 4 — write the first spec from the goal.
generate-agents
Command "generate-agents" from chohra-med/expo_boilerplate, covering invocation, how it works, the concern each agent gets (one per agent), rules for the injected block (every agent) and idempotent + the loop.
learn
Command "learn" from chohra-med/expo_boilerplate, covering command: learn — the learning loop (feedback → rules), when to run it, invocation, the loop (6 steps) and 1 — capture.
migrate
Command "migrate" from chohra-med/expo_boilerplate, covering invocation, steps and rule.