Review codebases for correctness, security, and architecture issues with prioritized findings.
npx skills add https://github.com/tcytan/tecton --skill review-code-tcytan
Please help me install this Agent Skill. Skill: review-code Source: https://github.com/tcytan/tecton/tree/main/.claude/skills/review-code Command: npx skills add https://github.com/tcytan/tecton --skill review-code-tcytan
This Skill reduces the risk of shipping defective or insecure code by producing structured, multi-dimensional review reports with prioritized, actionable findings.
Use it when you need repeatable engineering-quality assurance during code changes, audits, or pre-merge review—especially for small-to-medium codebases or focused path reviews.
Ask the AI to run a code review on the repository you want to assess, then review the generated review-report.md for must-fix issues.
High-intent search queries and answers about installing and using this skill.
To perform a structured code review, specify the target repository path. The workflow collects context, executes a quick risk scan, runs deep per-dimension analysis, and outputs a structured Markdown report with prioritized findings.
Multi-dimensional code review evaluates correctness, readability, performance, security, testing, and architecture issues. This structured approach prevents tunnel vision by assessing each dimension independently before consolidating prioritized findings.
Automated code review supports pre-merge risk triage by assigning consistent issue IDs and severity levels to detected security and correctness issues, enabling clear gating decisions before merging codebase changes.
The best way to generate a security audit report is running a state-driven workflow that performs quick scan risk detection and deep security analysis, producing a consolidated Markdown document with actionable findings.
The code review workflow operates without external dependencies. It requires only reading review specifications and executing internal workflow stages to assess the given codebase architecture and testing quality.
Automated code review is optimized for small-to-medium codebases or focused path reviews. For extremely large repositories, targeted directory specification is necessary to avoid exceeding context limits during deep analysis.
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I-OnlabsAudit codebases across architecture, quality, security, and performance to produce prioritized health reports.
addyosmaniReview code diffs for correctness, readability, architecture, security, and performance.
