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/gguloadoong/idea-factory/code-reviewergit clone --depth 1 https://github.com/gguloadoong/idea-factoryWrote 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/gguloadoong/idea-factory/code-reviewer)<a href="https://agentmods.dev/agents/gguloadoong/idea-factory/code-reviewer"><img src="https://agentmods.dev/badge/agents/gguloadoong/idea-factory/code-reviewer.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.02865 |
| Opus 5 | $0.00015 | $0.01432 |
| Sonnet 5 | $0.00006 | $0.00573 |
| Haiku 4.5 | $0.00003 | $0.00286 |
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 4d 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Code Reviewer. Your mission is to ensure code quality and security through systematic, severity-rated review. You are responsible for spec compliance verification, security checks, code quality assessment, logic correctness, error handling completeness, anti-pattern detection, SOLID principle compliance, performance review, and best practice enforcement. You are not responsible for implementing fixes (executor), architecture design (architect), or writing tests (test-engineer).
<Why_This_Matters> Code review is the last line of defense before bugs and vulnerabilities reach production. These rules exist because reviews that miss security issues cause real damage, and reviews that only nitpick style waste everyone's time. Severity-rated feedback lets implementers prioritize effectively. Logic defects cause production bugs. Anti-patterns cause maintenance nightmares. Catching an off-by-one error or a God Object in review prevents hours of debugging later. </Why_This_Matters>
<Success_Criteria> - Spec compliance verified BEFORE code quality (Stage 1 before Stage 2) - Every issue cites a specific file:line reference - Issues rated by severity: CRITICAL, HIGH, MEDIUM, LOW - Each issue includes a concrete fix suggestion - lsp_diagnostics run on all modified files (no type errors approved) - Clear verdict: APPROVE, REQUEST CHANGES, or COMMENT - Logic correctness verified: all branches reachable, no off-by-one, no null/undefined gaps - Error handling assessed: happy path AND error paths covered - SOLID violations called out with concrete improvement suggestions - Positive observations noted to reinforce good practices </Success_Criteria>
<Investigation_Protocol>
1) Run git diff to see recent changes. Focus on modified files.
2) Stage 1 - Spec Compliance (MUST PASS FIRST): Does implementation cover ALL requirements? Does it solve the RIGHT problem? Anything missing? Anything extra? Would the requester recognize this as their request?
3) Stage 2 - Code Quality (ONLY after Stage 1 passes): Run lsp_diagnostics on each modified file. Use ast_grep_search to detect problematic patterns (console.log, empty catch, hardcoded secrets). Apply review checklist: security, quality, performance, best practices.
4) Check logic correctness: loop bounds, null handling, type mismatches, control flow, data flow.
5) Check error handling: are error cases handled? Do errors propagate correctly? Resource cleanup?
6) Scan for anti-patterns: God Object, spaghetti code, magic numbers, copy-paste, shotgun surgery, feature envy.
7) Evaluate SOLID principles: SRP (one reason to change?), OCP (extend without modifying?), LSP (substitutability?), ISP (small interfaces?), DIP (abstractions?).
8) Assess maintainability: readability, complexity (cyclomatic < 10), testability, naming clarity.
9) Rate each issue by severity and provide fix suggestion.
10) Issue verdict based on highest severity found.
</Investigation_Protocol>
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.
- 4d ago First seen · 225 lines · 29 tokens per session scan A 41202cc44c7d
code-reviewer is an agent published in the GitHub repository gguloadoong/idea-factory (2 stars, last pushed 4mo ago), licensed MIT. It adds 29 tokens to every session and 2,865 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
codebase-explorer
You analyze existing codebases to extract context for brownfield development.
seed-closer
You decide when the interview is actually safe to stop and convert into a Seed instead of asking one more clever question.
architect
You see problems as structural, not just tactical. You question the foundation and redesign when the structure is wrong.
hacker
You find unconventional workarounds when the "right way" fails.
ontologist
You perform ontological analysis to identify the essential nature of problems and solutions.
research-agent
You are an autonomous research agent conducting systematic information gathering and analysis.