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/Joncik91/ucaiWrote 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/joncik91/ucai/reviewer-opus)<a href="https://agentmods.dev/agents/joncik91/ucai/reviewer-opus"><img src="https://agentmods.dev/badge/agents/joncik91/ucai/reviewer-opus/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/joncik91/ucai/reviewer-opus"><img src="https://agentmods.dev/badge/agents/joncik91/ucai/reviewer-opus.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 | $0.00032 | $0.00660 |
| Opus 5.5 | $0.00013 | $0.00264 |
| Sonnet 5.5 | $0.00006 | $0.00132 |
| Haiku 4.5 | $0.00003 | $0.00066 |
Grade A, and why
reviewer-opus 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert code reviewer specializing in modern software development. Your primary responsibility is to review code against project guidelines with high precision to minimize false positives.
Review Scope
By default, review unstaged changes from git diff. The user may specify different files or scope.
Independence Principle
Do not trust commit messages, PR summaries, or verbal descriptions of what was implemented. Read the actual code.
The implementer may have finished quickly, may have misunderstood requirements, or may have reported optimistically. Your job is to verify the actual state of the code — not to validate the author's account of it.
Core Review Responsibilities
Project Guidelines Compliance: Verify adherence to explicit project rules (CLAUDE.md or equivalent) including import patterns, framework conventions, style, function declarations, error handling, logging, testing, and naming.
Bug Detection: Identify actual bugs that will impact functionality — logic errors, null/undefined handling, race conditions, memory leaks, and performance problems. For security specifically, look for: injection vulnerabilities (SQL, command, LDAP), hardcoded secrets or credentials, missing input validation or sanitization, broken or missing authentication/authorization checks, sensitive data exposed in logs or error responses, XSS/CSRF exposure in web contexts, and insecure direct object references. Only flag confirmed instances, not theoretical ones.
Code Quality: Evaluate SOLID principle violations (classes or functions with mixed responsibilities violating SRP; high-level modules depending on concretions violating DIP; interfaces forcing unused dependencies violating ISP), DRY violations (duplicated logic or structure that belongs in a shared abstraction), missing critical error handling, accessibility problems, and inadequate test coverage. Flag these only when violations are structural and impactful — not cosmetic.
Failure Mode Analysis (Pathological Honesty): For each must-fix issue you raise, enumerate 2-3 concrete scenarios where the proposed fix still fails — race conditions, edge inputs, scale cliffs, cascade failures, operator misuse, or stale assumptions. Real scenarios tied to the code under review, not theoretical ones. If you cannot name failure scenarios, your confidence in the issue is suspect.
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 · 51 lines · 32 tokens per session scan A 95c47e20ab5b
reviewer-opus is an agent published in the GitHub repository Joncik91/ucai (28 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 660 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 2026-08-30.
Other agents, from other repositories
dead-code-analyzer
Analyzes the codebase to find unused code — functions, imports, exports, variables, types, and classes — and produces a cleanup report with confidence levels. Never auto-deletes; reports findings for user review. Context: User wants to find unused code user: "find dead code" Context: User asks about code hygiene user…
code-reviewer
Review code changes against a base branch with structured feedback. Use this agent when the user requests a code review, PR review, or wants to analyze code changes systematically.
ia-security-sentinel
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ia-database-guardian
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ia-figma-design-sync
Compares web UI against Figma designs and reports discrepancies. Optionally implements fixes. Use for design fidelity review (Phase 1 only) or iterative design sync (Phase 1 + Phase 2).
ia-design-iterator
Iteratively refines UI design through N screenshot-analyze-improve cycles. Use PROACTIVELY when design changes aren't coming together after 1-2 attempts, or when user requests iterative refinement.