Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ricneves-ai/flowgrammers-skillsnpx agentmods add skills/ricneves-ai/flowgrammers-skills/code-reviewerWrote 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/skills/ricneves-ai/flowgrammers-skills/code-reviewer)<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/code-reviewer"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/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/skills/ricneves-ai/flowgrammers-skills/code-reviewer"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/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 | $0.00075 | $0.01327 |
| Opus 5.5 | $0.00030 | $0.00531 |
| Sonnet 5.5 | $0.00015 | $0.00265 |
| Haiku 4.5 | $0.00007 | $0.00133 |
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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Reviewer
Ferramentas automatizadas de revisão de código para analisar pull requests, detectar problemas de qualidade de código e gerar relatórios de revisão.
Sumário
Ferramentas
PR Analyzer
Analisa o git diff entre branches para avaliar a complexidade de revisão e identificar riscos.
# Analisar branch atual contra main
python scripts/pr_analyzer.py /path/to/repo
# Comparar branches específicas
python scripts/pr_analyzer.py . --base main --head feature-branch
# Saída JSON para integração
python scripts/pr_analyzer.py /path/to/repo --json
O que detecta:
- Segredos hardcoded (senhas, chaves de API, tokens)
- Padrões de injeção SQL (concatenação de strings em consultas)
- Statements de depuração (debugger, console.log)
- Desabilitação de regras ESLint
- Tipos
anydo TypeScript - Comentários TODO/FIXME
A saída inclui:
- Pontuação de complexidade (1-10)
- Categorização de risco (crítico, alto, médio, baixo)
- Priorização de arquivos para ordem de revisão
- Validação de mensagem de commit
Code Quality Checker
Analisa código-fonte para problemas estruturais, code smells e violações SOLID.
# Analisar um diretório
python scripts/code_quality_checker.py /path/to/code
# Analisar linguagem específica
python scripts/code_quality_checker.py . --language python
# Saída JSON
python scripts/code_quality_checker.py /path/to/code --json
O que detecta:
- Funções longas (>50 linhas)
- Arquivos grandes (>500 linhas)
- God classes (>20 métodos)
- Aninhamento profundo (>4 níveis)
- Muitos parâmetros (>5)
- Alta complexidade ciclomática
- Tratamento de erro ausente
- Importações não utilizadas
- Números mágicos
Limites:
| Problema | Limite |
|---|---|
| Função longa | >50 linhas |
| Arquivo grande | >500 linhas |
| God class | >20 métodos |
| Muitos parâmetros | >5 |
| Aninhamento profundo | >4 níveis |
| Alta complexidade | >10 branches |
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 · 180 lines · 75 tokens per session scan A 9eeba9234959
code-reviewer is a skill published in the GitHub repository ricneves-ai/flowgrammers-skills (117 stars, last pushed 1mo ago), licensed MIT. It adds 75 tokens to every session and 1,327 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…