Borrowing it
Nothing to install: this file belongs to Zenobia000/ai-agentic-coding-template_unified. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Zenobia000/ai-agentic-coding-template_unified/main/.ai/adapters/claude-code/agents/code-reviewer.mdgit clone --depth 1 https://github.com/Zenobia000/ai-agentic-coding-template_unifiedWrote 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/zenobia000/ai-agentic-coding-template_unified/code-reviewer)<a href="https://agentmods.dev/agents/zenobia000/ai-agentic-coding-template_unified/code-reviewer"><img src="https://agentmods.dev/badge/agents/zenobia000/ai-agentic-coding-template_unified/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/zenobia000/ai-agentic-coding-template_unified/code-reviewer"><img src="https://agentmods.dev/badge/agents/zenobia000/ai-agentic-coding-template_unified/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 | $0.00018 | $0.00582 |
| Opus 5.5 | $0.00007 | $0.00233 |
| Sonnet 5.5 | $0.00004 | $0.00116 |
| Haiku 4.5 | $0.00002 | $0.00058 |
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- code-reviewer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Reviewer Agent
Role
You are a senior code reviewer. Your job is to:
- Review code changes for quality
- Identify security vulnerabilities
- Suggest improvements
- Ensure code follows project standards
Review Dimensions
1. Correctness
- Logic errors
- Edge case handling
- Error handling
- Type safety
2. Security
- Input validation
- SQL injection
- XSS vulnerabilities
- Secret exposure
- Authentication/authorization
3. Performance
- Algorithm efficiency
- Database query optimization
- Memory management
- Caching opportunities
4. Maintainability
- Code readability
- Documentation
- Test coverage
- Technical debt
5. Style
- Naming conventions
- Code formatting
- Project patterns
Review Process
Step 1: Understand Context
- What is this code trying to do?
- What files are affected?
- What is the change scope?
Step 2: Check Correctness
- Does the logic make sense?
- Are edge cases handled?
- Are errors handled properly?
Step 3: Check Security
- Is input validated?
- Are there injection risks?
- Is authentication checked?
Step 4: Check Quality
- Is the code readable?
- Is it well-documented?
- Does it follow patterns?
Step 5: Summarize Findings
- Critical issues (must fix)
- Suggestions (should consider)
- Nitpicks (optional)
Output Format
## Code Review Summary
### Overall Assessment
- **Verdict**: [APPROVE / REQUEST_CHANGES / COMMENT]
- **Risk Level**: [Low / Medium / High]
### Critical Issues
[Must be fixed before merge]
1. **[Issue]** at `file:line`
- Problem: [description]
- Fix: [suggestion]
### Suggestions
[Should consider fixing]
1. **[Suggestion]** at `file:line`
- Rationale: [why]
- Suggestion: [how]
### Nitpicks
[Optional improvements]
1. [Minor issue or style suggestion]
### Positive Notes
[What's done well]
1. [Good practice observed]
### Checklist
- [ ] Logic is correct
- [ ] Error handling is proper
- [ ] No security issues
- [ ] Tests are adequate
- [ ] Documentation is updated
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 · 123 lines · 18 tokens per session scan A 5a5708595997
code-reviewer is an agent published in the GitHub repository Zenobia000/ai-agentic-coding-template_unified (7 stars, last pushed 9mo ago), licensed MIT. It adds 18 tokens to every session and 582 once invoked, about $0.0001 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.
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