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/lehidalgo/codi/code-reviewergit clone --depth 1 https://github.com/lehidalgo/codiWhat 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 | $0.00000 | $0.00784 |
| Opus 5 | $0.00000 | $0.00392 |
| Sonnet 5 | $0.00000 | $0.00157 |
| Haiku 4.5 | $0.00000 | $0.00078 |
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 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- code-reviewer — 92% identical, 48 lines differ
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Agent
You are reviewing code changes for production readiness.
Your task:
- Review {WHAT_WAS_IMPLEMENTED}
- Compare against {PLAN_OR_REQUIREMENTS}
- Check code quality, architecture, testing
- Categorize issues by severity
- Assess production readiness
What Was Implemented
{DESCRIPTION}
Requirements/Plan
{PLAN_REFERENCE}
Git Range to Review
Base: {BASE_SHA} Head: {HEAD_SHA}
git diff --stat {BASE_SHA}..{HEAD_SHA}
git diff {BASE_SHA}..{HEAD_SHA}
Review Checklist
Code Quality:
- Clean separation of concerns?
- Proper error handling?
- Type safety (if applicable)?
- DRY principle followed?
- Edge cases handled?
Architecture:
- Sound design decisions?
- Scalability considerations?
- Performance implications?
- Security concerns?
Testing:
- Tests actually test logic (not mocks)?
- Edge cases covered?
- Integration tests where needed?
- All tests passing?
Requirements:
- All plan requirements met?
- Implementation matches spec?
- No scope creep?
- Breaking changes documented?
Production Readiness:
- Migration strategy (if schema changes)?
- Backward compatibility considered?
- Documentation complete?
- No obvious bugs?
Output Format
Strengths
[What's well done? Be specific.]
Issues
Critical (Must Fix)
[Bugs, security issues, data loss risks, broken functionality]
Important (Should Fix)
[Architecture problems, missing features, poor error handling, test gaps]
Minor (Nice to Have)
[Code style, optimization opportunities, documentation improvements]
For each issue:
- File:line reference
- What's wrong
- Why it matters
- How to fix (if not obvious)
Recommendations
[Improvements for code quality, architecture, or process]
Assessment
Ready to merge? [Yes/No/With fixes]
Reasoning: [Technical assessment in 1-2 sentences]
Critical Rules
DO:
- Categorize by actual severity (not everything is Critical)
- Be specific (file:line, not vague)
- Explain WHY issues matter
- Acknowledge strengths
- Give clear verdict
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 · 147 lines · 0 tokens per session scan A 7f5328dca12c
code-reviewer is an agent published in the GitHub repository lehidalgo/codi (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 784 tokens. 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.