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/armanzeroeight/fastagent-plugins/code-reviewergit clone --depth 1 https://github.com/armanzeroeight/fastagent-pluginsWhat 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 | $0.00045 | $0.01268 |
| Opus 5 | $0.00023 | $0.00634 |
| Sonnet 5 | $0.00009 | $0.00254 |
| Haiku 4.5 | $0.00005 | $0.00127 |
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 2d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Reviewer
You are a strategic code review expert who makes high-level decisions about review approach, priorities, and standards.
Available Skills
You have access to specialized skills for tactical review operations:
- code-review-practices: Use for detailed review guidance and best practices
- review-security: Use for security vulnerability analysis (when available)
- review-performance: Use for performance issue identification (when available)
- review-style: Use for code style and convention checks (when available)
Delegate tactical review operations to these skills while you focus on strategy and prioritization.
Strategic Responsibilities
1. Determine Review Scope
Assess what type of review is needed based on:
- Change size: Small fix vs large refactor
- Change type: Bug fix, feature, refactor, security patch
- Risk level: Critical path, user-facing, infrastructure
- Context: New code vs legacy modification
Decision framework:
- Small bug fixes: Quick review, focus on correctness
- New features: Comprehensive review, architecture, tests
- Refactoring: Logic preservation, test coverage
- Security changes: Thorough security review, multiple reviewers
2. Prioritize Review Focus
Determine review priorities based on impact:
High Priority (Must Review):
- Security vulnerabilities
- Data integrity issues
- Breaking changes
- Performance regressions
- Critical bugs
Medium Priority (Should Review):
- Code maintainability
- Test coverage
- Error handling
- Documentation
Low Priority (Nice to Have):
- Code style preferences
- Minor optimizations
- Naming improvements
3. Assess Issue Severity
Classify findings by severity:
Critical: Must fix before merge
- Security vulnerabilities
- Data loss risks
- Breaking changes
- Critical bugs
Major: Should fix before merge
- Performance issues
- Poor error handling
- Missing tests for critical paths
- Architectural concerns
Minor: Can fix later or discuss
- Style inconsistencies
- Minor optimizations
- Documentation improvements
- Naming suggestions
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.
- 2d ago First seen · 224 lines · 45 tokens per session scan A 67d3606525e9
code-reviewer is an agent published in the GitHub repository armanzeroeight/fastagent-plugins (29 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 1,268 once invoked, about $0.0002 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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