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code-reviewer
Automated code review with customizable quality rules
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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Automated code review with customizable quality rules
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | code-reviewer |
| description | Automated code review with customizable quality rules |
| version | 1.3.0 |
| author | go-on-team |
| tags | ["code","review","quality","rust","python","typescript","go"] |
| min_go_on_version | 1.0.0 |
Automated code review that checks for common issues, style violations, and potential bugs across multiple programming languages. Reviews are returned as structured feedback with severity levels and line references.
error for definite bugs, warning for style/correctness concerns, and suggestion for improvements.| Parameter | Type | Description |
|---|---|---|
code | string | Source code to review |
language | string | Programming language (rust, python, typescript, go, java, cpp) |
rules | string[] | Optional: specific rule categories to check (e.g. naming, documentation, error-handling, security, performance) |
{
"code": "fn add(a: i32, b: i32) -> i32 { a + b }",
"language": "rust",
"rules": ["naming", "documentation"]
}
{
"score": 0.85,
"summary": "Minor documentation issues found",
"findings": [
{
"line": 1,
"column": 1,
"severity": "suggestion",
"rule": "documentation",
"message": "Function `add` is missing doc comment",
"suggestion": "Add a `///` doc comment describing the function's purpose, arguments, and return value"
},
{
"line": 1,
"column": 3,
"severity": "suggestion",
"rule": "naming",
"message": "Parameter `a` has a short name; consider a more descriptive identifier",
"suggestion": "Rename `a` to something meaningful like `left` or `augend`"
}
],
"language": "rust",
"total_lines": 1
}
Analyzes project structure, module dependencies, imports, and entry points to generate architecture diagrams in Mermaid format
Analyzes ETL and data pipeline code for optimization opportunities across Python (Pandas, PySpark), Rust (polars, datafusion), SQL, and general pipeline descriptions
Validates environment variable configurations and config files (YAML, TOML, JSON, .env) for missing required variables, type mismatches, deprecated keys, naming convention violations, secret exposure risks, and invalid value ranges
Analyzes code for performance bottlenecks including N+1 queries, O(n^2) or worse algorithms, unnecessary allocations, sync I/O in async contexts, excessive cloning, missing caching opportunities, and large payload transfers. Supports Rust, Python, TypeScript, and Go.
Analyzes, improves, and restructures LLM prompts for clarity, efficiency, and reliability
Analyzes source code for common security vulnerabilities including SQL injection, XSS, command injection, hardcoded secrets, insecure deserialization, path traversal, and SSRF