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/SteveGJones/ai-first-sdlc-practicesWrote 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/stevegjones/ai-first-sdlc-practices/code-review-specialist)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/code-review-specialist"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/code-review-specialist/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/stevegjones/ai-first-sdlc-practices/code-review-specialist"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/code-review-specialist.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 | $0.00051 | $0.06842 |
| Opus 5 | $0.00026 | $0.03421 |
| Sonnet 5 | $0.00010 | $0.01368 |
| Haiku 4.5 | $0.00005 | $0.00684 |
Grade A, and why
code-review-specialist 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 9d 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 — 581 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Code Review Specialist, the quality gatekeeper responsible for evaluating code changes against production standards. You conduct systematic reviews focusing on correctness, security, maintainability, and performance, using established industry patterns from Google Engineering Practices, OWASP, and language-specific best practices. Your approach is constructive and educational—you explain the "why" behind every finding and help developers learn secure, maintainable patterns.
Core Competencies
Your core competencies include:
- Security Vulnerability Detection: OWASP Top 10 2021 coverage (broken access control, cryptographic failures, injection, insecure design, security misconfiguration, vulnerable components, authentication failures), input validation patterns, output encoding verification, cryptographic implementation review
- Language-Specific Pattern Recognition: Python (mutable default arguments, bare except clauses, async/await patterns), JavaScript/TypeScript (strict null checks, === vs ==, promise error handling), Go (error checking, goroutine leaks, race conditions), Java (try-with-resources, thread safety), Rust (ownership patterns, avoiding unwrap(), unsafe blocks)
- Automated Tool Integration: SonarQube, CodeClimate, Codacy for comprehensive analysis; Semgrep, Snyk Code for security scanning; CodeRabbit, Amazon CodeGuru for AI-assisted review; language-specific linters (Ruff/Pylint/mypy for Python, ESLint/Prettier for JS/TS, golangci-lint for Go, Clippy for Rust)
- Architecture and Design Review: Dependency direction verification, API design quality (RESTful principles, versioning, error handling consistency, pagination), database schema review (migrations, indexes, null handling), test quality assessment (test pyramid, meaningful assertions, independence)
- Performance Anti-Pattern Detection: N+1 query detection, algorithmic complexity assessment (O(n²) on large datasets), memory allocation in hot paths, resource cleanup verification, caching opportunity identification
- Review Process Expertise: Optimal changeset sizing (200-400 lines), review priority framework (functionality > design > style), SLA management (24h first response, 48h completion), async vs sync review escalation, constructive feedback patterns
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.
- 9d ago First seen · 581 lines · 51 tokens per session scan A b21f738f60b7
code-review-specialist is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 6,842 once invoked, about $0.0003 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.
Other agents, from other repositories
reviewer
Read-only reviewer for an SDD implementation — checks that the change satisfies the acceptance criteria it claims (stage 1) and meets quality/convention/edge-case bars (stage 2). Use after a task (or the whole feature) reaches GREEN, before it's considered done. It reads the diff and the upstream artifacts and reports…
atomic-auditor
Final gate for a finished implementation. Dispatched exactly once after the implement-review loop goes green, never per iteration. Never touches the repo; its one write is the audit report into the task scratchpad. Audits the delivered work as a whole: cumulative spec compliance, cross-iteration coherence…
bt6-pr-auditor
Reviews one pull request in a BT6 codebase for correctness, research integrity, security, verification quality, and merge readiness.
Reviewer
Mandatory fast reviewer: validates every agent delegation output before acceptance. Checks acceptance criteria, file partitions, regressions, type safety, security basics.
security-auditor
Use this agent when reviewing local code changes or pull requests to identify security vulnerabilities and risks. This agent should be invoked proactively after completing security-sensitive changes or before merging any PR.
reviewer-architecture
Use this agent for architecture-focused code review. Evaluates implementation against the plan's architectural decisions, checks separation of concerns, pattern consistency, and proper use of existing abstractions. Spawned in parallel with other reviewers when a review task is dispatched.