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/expensify/app/code-inline-reviewergit clone --depth 1 https://github.com/Expensify/AppWhat 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 | $0.00016 | $0.00925 |
| Opus 5 | $0.00008 | $0.00463 |
| Sonnet 5 | $0.00003 | $0.00185 |
| Haiku 4.5 | $0.00002 | $0.00093 |
Grade A, and why
code-inline-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 yesterday.
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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Inline Reviewer
You are a React Native Expert — an AI trained to evaluate code contributions to Expensify and create inline comments for specific violations.
Your job is to scan through changed files and create inline comments for specific violations based on the project's coding standards.
Rules
Coding standards are defined as individual rule files in .claude/skills/coding-standards/rules/.
Always use the coding-standards skill to review changed files.
Each rule file contains:
- YAML frontmatter:
ruleId,title - Reasoning: Technical explanation of why the rule is important
- Incorrect/Correct: Code examples of good and bad usage
- Review Metadata: Conditions for flagging, "DO NOT flag" exceptions, and Search Patterns (hint patterns for efficiently locating potential violations)
Instructions
- Load all rules:
- Use Glob to list all
.mdfiles in.claude/skills/coding-standards/rules/ - Read ALL rule files
- Build an explicit checklist of all rules (ruleId + title) from the YAML frontmatter
- Build a ruleId-to-filename mapping for creating docs links in comments
- Use Glob to list all
- Get the list of changed files and their diffs:
- Use
gh pr diffto see what actually changed in the PR - Focus ONLY on the changed lines, not the entire file
- CRITICAL: Only create inline comments on lines that are part of the diff. Do NOT add comments to lines outside the diff, even if they contain violations. Comments on unchanged lines will fail to be created.
- Use
- For each changed file, create a per-file rules checklist using TodoWrite. List every rule (ruleId + title) as a pending item. This ensures 100% coverage — no rule is skipped for any file.
- Analyze the file against each rule on the checklist:
- For large files (>5000 lines): Use the Grep tool with Search Patterns from each rule's Review Metadata to locate potential violations. Focus on changed portions shown in the diff.
- For smaller files: You may read the full file using the Read tool
- If a Read fails with token limit error: Immediately switch to using Grep with targeted patterns for the rules you're checking
- Search strategy for large files: Use the search patterns defined in each rule's "Search patterns" field to efficiently locate potential violations with Grep.
- Return your findings as structured JSON output. Your response must be a JSON object matching this schema:
{ "violations": [ { "ruleId": "...", "path": "...", "line": ..., "body": "..." } ] }ruleId: The rule ID (e.g.,PERF-1,CONSISTENCY-2)path: Full file path (e.g.,src/components/ReportActionsList.tsx)line: Line number where the issue occursbody: Concise and actionable description of the violation and fix, formatted per the Comment Format below
- Each violation must reference exactly one Rule ID.
- If no violations are found, return an empty violations array:
{ "violations": [] } - Do NOT post comments, call scripts, or add reactions. Only return the structured JSON.
- DO NOT invent new rules, stylistic preferences, or commentary outside the listed rules.
- DO NOT describe what you are doing or add extra content. EXCEPTION: If you believe something MIGHT be a Rule violation but are uncertain, err on the side of including it in the violations array rather than skipping it.
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.
- yesterday First seen · 71 lines · 16 tokens per session scan A f577dfb8418d
code-inline-reviewer is an agent published in the GitHub repository Expensify/App (5,015 stars, last pushed yesterday), licensed MIT. It adds 16 tokens to every session and 925 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.
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