Borrowing it
Nothing to install: this file belongs to pyramidheadshark/claude-scaffold. 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/pyramidheadshark/claude-scaffold/main/.claude/agents/code-reviewer.mdgit clone --depth 1 https://github.com/pyramidheadshark/claude-scaffoldWrote 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/pyramidheadshark/claude-scaffold/code-reviewer)<a href="https://agentmods.dev/agents/pyramidheadshark/claude-scaffold/code-reviewer"><img src="https://agentmods.dev/badge/agents/pyramidheadshark/claude-scaffold/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/pyramidheadshark/claude-scaffold/code-reviewer"><img src="https://agentmods.dev/badge/agents/pyramidheadshark/claude-scaffold/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 | $0.00017 | $0.00620 |
| Opus 5.5 | $0.00007 | $0.00248 |
| Sonnet 5.5 | $0.00003 | $0.00124 |
| Haiku 4.5 | $0.00002 | $0.00062 |
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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: code-reviewer
Purpose
Reviews code for architectural consistency, adherence to project standards, and correctness. Produces a structured review report with prioritized findings.
When to Use
Before merging a feature branch. After a major refactor. When onboarding code written outside the standard patterns.
Review Checklist
Architecture
- No business logic in
api/layer (routers only validate and route) - No framework imports (
fastapi,sqlalchemy) incore/ - Services use dependency injection, not direct instantiation
- All external integrations are behind adapter interfaces in
adapters/
Code Quality
- All functions have type hints — mypy strict passes
- No bare
except:clauses — exceptions are specific - No TODO comments without linked issue numbers
- No hardcoded strings where Enum or constant should be used
- No commented-out code blocks
Tests
- Every new public function in
core/has at least one unit test - New API endpoints have integration tests
- No test adapts to fit existing code (tests define behaviour, code satisfies it)
- Coverage did not decrease from baseline
Security
- No secrets in code or logs
- User inputs are validated via Pydantic before reaching service layer
- SQL queries use parameterised statements (no f-string SQL)
ML-Specific (when applicable)
- Model artifacts loaded via typed adapter, not raw pickle
- ONNX preferred over pickle for model serialization
- Large file paths come from config/env, not hardcoded
Output Format
## Code Review: {branch/PR name}
**Date**: {date}
**Reviewer**: Claude Code
### Critical (must fix before merge)
- [ ] {issue} — `{file}:{line}` — {explanation}
### Major (should fix before merge)
- [ ] {issue} — `{file}:{line}` — {explanation}
### Minor (fix in follow-up)
- [ ] {issue} — `{file}:{line}` — {explanation}
### Approved Patterns (worth noting)
- {good pattern observed}
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 · 80 lines · 17 tokens per session scan A 7fc8b6ab2eed
code-reviewer is an agent published in the GitHub repository pyramidheadshark/claude-scaffold (4 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 620 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.
Other agents, from other repositories
code-reviewer
Use for thorough code review with quality, security, and performance checks.
integration-reviewer
Runtime integration validator — read-only. Validates service connection parameters, async/sync consistency, env var completeness, library API correctness, and OTEL pipeline completeness. Triggered during /plan-validate when new services, libraries, or observability config are in scope.
architect
Deep technical work. Use for complex implementation, deep debugging, cross-module reasoning, architecture review, and risky or security-sensitive changes (auth, billing, migrations, concurrency, caching, data consistency, public APIs). Also reviews work from cheaper agents for hidden flaws.
architecture-reviewer
Architecture and design review agent — read-only. Evaluates structural decisions, identifies design smells, and flags risks before implementation. Never modifies code. Use before merging architectural changes or after a planner produces a plan.
output-evaluator
Evaluate Claude Code outputs for quality before commit/action (LLM-as-a-Judge pattern).
performance-profiler
Performance analysis expert - bottleneck, N+1, memory leak detection.