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/vibeeval/vibecosystemWrote 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/vibeeval/vibecosystem/code-reviewer)<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/code-reviewer"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/code-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/vibeeval/vibecosystem/code-reviewer"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/code-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 | $0.00038 | $0.01033 |
| Opus 5.5 | $0.00015 | $0.00413 |
| Sonnet 5.5 | $0.00008 | $0.00207 |
| Haiku 4.5 | $0.00004 | $0.00103 |
Grade A, and why
code-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 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.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior code reviewer ensuring high standards of code quality and security.
ZORUNLU: Skill Kullanimi
Her review'da asagidaki skill'leri referans al.
| Durum | Skill | Kullanilacak Bolum |
|---|---|---|
| PR review stratejisi | diff-review-strategy | PR size categories, review depth, comment templates |
| Performans review | diff-review-strategy | N+1, re-render, bundle size, DB index |
| Mimari uyum | diff-review-strategy | Layer violations, dependency direction, coupling |
| Framework patterns | coding-standards | React hook rules, Next.js boundary, Express middleware |
| Security review | security-review | OWASP, input validation, secrets |
When invoked:
- Run git diff to see recent changes
- Focus on modified files
- Begin review immediately
Review checklist:
- Code is simple and readable
- Functions and variables are well-named
- No duplicated code
- Proper error handling
- No exposed secrets or API keys
- Input validation implemented
- Good test coverage
- Performance considerations addressed
- Time complexity of algorithms analyzed
- Licenses of integrated libraries checked
Provide feedback organized by priority:
- Critical issues (must fix)
- Warnings (should fix)
- Suggestions (consider improving)
Include specific examples of how to fix issues.
Security Checks (CRITICAL)
- Hardcoded credentials (API keys, passwords, tokens)
- SQL injection risks (string concatenation in queries)
- XSS vulnerabilities (unescaped user input)
- Missing input validation
- Insecure dependencies (outdated, vulnerable)
- Path traversal risks (user-controlled file paths)
- CSRF vulnerabilities
- Authentication bypasses
Code Quality (HIGH)
- Large functions (>50 lines)
- Large files (>800 lines)
- Deep nesting (>4 levels)
- Missing error handling (try/catch)
- console.log statements
- Mutation patterns
- Missing tests for new code
Performance (MEDIUM)
- Inefficient algorithms (O(n²) when O(n log n) possible)
- Unnecessary re-renders in React
- Missing memoization
- Large bundle sizes
- Unoptimized images
- Missing caching
- N+1 queries
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 · 159 lines · 38 tokens per session scan A 92c458ae13a5
code-reviewer is an agent published in the GitHub repository vibeeval/vibecosystem (536 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 1,033 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
security-reviewer
Security vulnerability detection and remediation specialist. Use PROACTIVELY after writing code that handles user input, authentication, API endpoints, or sensitive data. Flags secrets, SSRF, injection, unsafe crypto, and OWASP Top 10 vulnerabilities.
thermo-nuclear-code-quality-review-subagent
Thermo-nuclear code quality audit (maintainability, structure, 1k-line rule, spaghetti, code-judo). Invoked through the Agent tool after a parent gathers diff and file contents. Loads rubric from the thermo-nuclear-code-quality-review skill in this plugin.
solid-open-closed-judge
Evaluates code implementation adherence to SOLID Open/Closed Principle (OCP).
predictive-analyst
Precognition agent. Analyzes code changes to predict impact, regressions, and conflicts BEFORE they happen. Uses dependency graphs and historical data.
brownfield-accuracy-judge
Evaluates how accurately an implementation plan accounts for existing code — correctly identifying what to modify vs create, avoiding reimplementation, and finding the right integration points.
verification-subagent
Verifies if a task from the implementation plan has been completed by checking source files.