What is the 3-pass auditable review mode?

The 3-pass mode is a systematic process for modules where the AI reads every file three times: first for correctness, second for security, and third for architecture, ensuring complete coverage without skipping files.

How does the confidence scoring filter results?

To ensure accuracy, the skill assigns a confidence score (0-100) to every finding. Only issues with a confidence of 75% or higher are included in the final report to prevent false positives.

Can I save the code review results to a file?

Yes, by including the --file flag in your command, the skill will automatically generate a REVIEW.md file in your project root containing the full report.

What dimensions are covered in the review rubric?

The review evaluates code across six key areas: Code Quality, Security (including OWASP-style vulnerabilities), Architecture, Performance, Testing Gaps, and Documentation.

Lore Code Review

Name: Lore Code Review
Author: LayerDynamics

byLayerDynamics

0•

Security & Testing

Performs structured, multi-scope code reviews using a rigorous 3-pass auditable workflow to identify security vulnerabilities and architectural flaws.

Lore Code Review is a specialized skill for Claude Code that enables deterministic and repeatable code audits. It moves beyond simple suggestions by offering four distinct review modes: targeted file review, a comprehensive 3-pass module audit that ensures 100% file coverage, full-project structural analysis, and agent-dispatched topic investigations. Every review follows a standardized rubric covering code quality, security, architecture, performance, testing, and documentation, ensuring that findings are objective, evidence-based, and prioritized by confidence and severity.

Key Features

01Systematic 3-pass auditable workflow for guaranteed file coverage

02Multi-mode review scopes (Files, Module, Project, and Topic-based)

030 GitHub stars

04Comprehensive 6-dimension evaluation rubric including Security and Architecture

05Evidence-based confidence scoring to eliminate AI hallucinations and noise

06Standardized markdown reporting with actionable verification checklists

Use Cases

01Conducting targeted reviews of specific file changes before pull request submission

02Generating high-level architectural assessments of entire project codebases

03Performing deep security and logic audits on mission-critical modules

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add layerdynamics/lore review

For use in Claude.ai and ChatGPT