Analyze codebase patterns and conventions to guide safe changes.
npx skills add https://github.com/MrLesk/agents-council --skill context-hunter
Please help me install this Agent Skill. Skill: context-hunter Source: https://github.com/MrLesk/agents-council/tree/main/.codex/skills/context-hunter Command: npx skills add https://github.com/MrLesk/agents-council --skill context-hunter
Discover patterns, conventions, and unwritten rules in a codebase to guide safer, faster changes.
Ask the AI to scan the repository for existing patterns, naming conventions, and unwritten rules and summarize findings before starting work.
High-intent search queries and answers about installing and using this skill.
Codebase pattern discovery works by analyzing naming conventions, data flows, schema usage, and test patterns across a project. It surfaces actionable guidance on unwritten rules so you can validate assumptions and maintain consistency before implementing features or fixes.
The best way to analyze naming conventions and data flows is to scan the repository for established patterns and testing norms. This detects architectural norms and schema usage, providing actionable guidance to reduce duplication and maintain consistency during development.
Yes, you can validate assumptions by scanning the project for existing patterns, naming schemes, and data flows. This surfaces potential inconsistencies and unwritten rules before implementation, ensuring your bug fix aligns with established conventions.
Ensure consistency by analyzing the codebase for existing naming schemes, data flows, and test patterns before implementation. This surfaces unwritten rules and architectural norms, guiding your feature development to align safely with the project's established conventions.
You should scan for test patterns and schema usage before refactoring or adding features. This detects established conventions and recurring solutions, surfacing actionable guidance to prevent inconsistencies and ensure new code aligns with existing data flows.
opendatahub-ioCreates a depth-1 clone of a Git repository in a temporary location.
otahontasIdentify architectural patterns, naming conventions, and data flow across modules.
nobelkReproduce bugs with failing tests and verify fixes via the full test suite.
ArabelaTsoAnalyze Python codebases to identify component boundaries and detect architectural violations.
