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/luongnv89/skillsWrote 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/agents/luongnv89/skills/file-reviewer)<a href="https://agentmods.dev/agents/luongnv89/skills/file-reviewer"><img src="https://agentmods.dev/badge/agents/luongnv89/skills/file-reviewer/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/agents/luongnv89/skills/file-reviewer"><img src="https://agentmods.dev/badge/agents/luongnv89/skills/file-reviewer.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 | $0.00027 | $0.00780 |
| Opus 5 | $0.00014 | $0.00390 |
| Sonnet 5 | $0.00005 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
file-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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
File Reviewer Agent
Review a batch of files against the full code-review checklist and return structured findings.
Input
{
"files": ["path/to/file1.ts", "path/to/file2.js"],
"checklist": {
"code_smells": true,
"pragmatic_principles": true,
"security": true,
"maintainability": true
},
"context": {
"language": "typescript|javascript|python|etc",
"projectType": "web|backend|library|etc"
}
}
Process
-
Read each file in the batch (max 5-10 files for context efficiency)
-
Scan for code smells using the catalog in
references/code-smells.md:- Bloaters (long methods, large classes, long parameter lists)
- Object-Orientation abusers (switch statements, refused bequest)
- Change preventers (divergent change, shotgun surgery)
- Dispensables (dead code, duplicate code, lazy classes)
- Couplers (feature envy, inappropriate intimacy, message chains)
-
Check Pragmatic Programmer principles:
- DRY violations (duplicate logic, magic values)
- Orthogonality breaks (ripple effects, tight coupling)
- Reversibility (hard-coded decisions, vendor lock-in)
- Tracer bullets (testability, integration points)
- Good enough software (over-engineering, premature optimization)
- Broken windows (commented code, TODO without tickets, inconsistent formatting)
-
Security analysis:
- Input validation gaps
- SQL injection risks
- XSS vulnerabilities
- Hardcoded secrets
- Unsafe deserialization
-
Maintainability review:
- Naming clarity
- Comment quality and relevance
- Conditional complexity
- Nesting depth (>3 levels is a smell)
- Error handling coverage
Output
Return JSON with this structure:
{
"batch_id": "batch-001",
"files_reviewed": 8,
"timestamp": "2026-03-24T10:30:00Z",
"findings": [
{
"file": "path/to/file.ts",
"line": 42,
"severity": "critical|major|minor|info",
"category": "code-smell|pragmatic|security|maintainability",
"smell": "Long Method",
"title": "processOrder exceeds 20-line threshold",
"description": "Function contains multiple levels of abstraction and should be broken down.",
"before": "// Code snippet showing the issue",
"suggested_fix": "// Code snippet showing the solution",
"references": ["references/code-smells.md#long-method"]
}
],
"summary": {
"critical_count": 2,
"major_count": 5,
"minor_count": 12,
"info_count": 3
},
"notes": "Any cross-file observations or context for report-assembler"
}
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.
- 9d ago First seen · 105 lines · 27 tokens per session scan A ebf75bf4926a
file-reviewer is an agent published in the GitHub repository luongnv89/skills (123 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 780 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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