speckit-review-code

Review code changes for guideline compliance and bugs with confidence scoring.

1|Updated Mar 27, 2026
One-click install
npx skills add https://github.com/payangar-dev/texlab --skill speckit-review-code-payangar-dev
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: speckit-review-code
Source: https://github.com/payangar-dev/texlab/tree/main/.agents/skills/speckit-review-code
Command: npx skills add https://github.com/payangar-dev/texlab --skill speckit-review-code-payangar-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you quickly identify genuine code quality issues and non-compliance with your project’s review guidelines, reducing regressions and reviewer thrash.

Core Features & Use Cases

  • Project-guideline compliance review: Checks adherence to explicit rules (style, conventions, error handling, naming, imports, framework practices) using the project’s stored constitution/instructions.
  • High-confidence bug detection: Finds actual functional, security, and reliability problems (logic errors, missing critical handling, race/performance issues) while filtering out likely false positives.
  • Severity-scored reporting: Outputs only issues with confidence ≥ 80, grouped by criticality, with file paths, line numbers, and concrete fix suggestions.

Use Case: Reviewing a pull request where you want assurance that changes follow .specify/memory/constitution.md/CLAUDE-style rules and don’t introduce subtle correctness or robustness bugs.

Quick Start

Ask the AI to review your current changes for only high-confidence guideline and bug issues using the speckit-review-code skill.

Frequently Asked Questions about speckit-review-code

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review a pull request for code quality and guideline compliance?

Pull request code review involves checking changes against project guidelines and detecting bugs with high confidence. This skill targets working-tree changes, enforcing a confidence threshold of 80 to produce severity-grouped findings with file paths and actionable fixes.

What is static analysis confidence scoring and how does it filter code review issues?

Static analysis confidence scoring rates the certainty of detected code issues to filter false positives. This skill enforces a minimum confidence threshold of 80, outputting only severity-grouped findings for genuine bugs and guideline non-compliance with specific file paths and line numbers.

How do I enforce project-specific coding conventions and error handling rules during code review?

To enforce project-specific coding conventions, the skill checks changes against stored constitution or CLAUDE-style instructions within the `.specify/` structure. It validates adherence to explicit rules for style, naming, imports, and error handling, reporting violations with concrete fix suggestions.

Does this code review skill work with my spec-kit project structure?

Yes, this code review skill works with spec-kit project structures. It specifically targets projects containing the expected `.specify/` directory structure to review pull request and working-tree changes against stored guidelines like `constitution.md`.

What is the best way to catch functional and security bugs early in pull request changes?

The best way to catch functional and security bugs early is through high-confidence bug detection on pull request changes. This skill identifies actual logic errors, missing critical handling, and race or performance issues while filtering out likely false positives via an 80 confidence threshold.

Why does my static analysis report so many false positives during issue triage?

Static analysis reports many false positives during issue triage because unfiltered tools flag every potential match. This skill reduces false positives by enforcing a confidence threshold of at least 80, ensuring only high-certainty bugs and guideline violations are reported with actionable fixes.