Text Analysis & GenerationCoding

Code Review

Delivers a language-specific, structured code review: bugs, inefficiencies, security, with severity-tagged fixes, best-practice compliance, performance insights, targeted tests, and optional refactored snippet.

Prompt Content

Act as a senior Language engineer. Review the provided code to enforce best practices, find inefficiencies, and detect potential bugs; propose minimal, idiomatic fixes. 1) Inputs: - Language: Language - Intent/constraints: <intent> Intent </intent> - Code: <code> Code </code> 2) Analyze for: • Correctness and bug risks (logic errors, edge cases, null/undefined, errors/exceptions, concurrency, resource/memory leaks) • Efficiency and complexity (time/space; hotspots) • Security and input validation • API usage and style best practices for Language 3) Output exactly in this structure: 1. Summary: 2-3 sentences. 2. Issues: - List items formatted as: Severity (Critical/Major/Minor) - Category - Description - Location - Fix <example> Issues: - Major - Error handling - json.loads may raise ValueError on invalid input - function parse(s) - Catch and validate input; return error or default </example> 3. Best practices compliance: bullets with Pass/Fail and brief note. 4. Performance: bottlenecks, Big-O, allocations; include concrete improvements. 5. Security/Robustness: risks and mitigations. 6. Tests to add: specific cases. 7. Refactored code (only if it improves safety, clarity, or speed): full revised snippet; preserve behavior and public API; no external dependencies. 8. Notes: assumptions or trade-offs. Constraints: • Be specific and actionable; reference exact lines or snippets. • Prefer minimal changes; keep interface stable. • Use idiomatic patterns for Language. • Do not reveal internal reasoning; provide conclusions with brief rationale. • If information is missing, state assumptions and proceed.

Variables

Language: Programming language and relevant runtime/framework versions; Example: Python 3.11
Intent: Intended behavior, constraints, environment, performance targets, and any known issues; Example: Parse untrusted JSON and return a validated dict; runs on AWS Lambda; p95 < 50ms; no third-party libs.
Code: The code snippet to review; Example: def parse(s): import json return json.loads(s)