python-plan-optimization
6-phase read-only Python analysis workflow that identifies design principle violations, code smells, and modernization opportunities based on specific project types (POC to Open Source).
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
545 skills found
6-phase read-only Python analysis workflow that identifies design principle violations, code smells, and modernization opportunities based on specific project types (POC to Open Source).
Reliably rotate images by 90-degree increments using a deterministic Python script. Supports PNG, JPG, GIF, BMP, and TIFF, preserving quality with automated file handling.
Extract tacit engineering knowledge through guided interviews and generate structured steerings for consistent project standards and conventions.
Design professional-grade brand identities using geometric primitives, negative space, and flat vector-style aesthetics via AI-driven branding logic.
Cascading goal tracking system connecting 3-year vision to daily tasks. Automates progress calculation, stalled goal detection, and project-to-goal alignment for Obsidian vaults.
Search, analyze, and audit GeminiClaw session logs and memory. Use to investigate past interactions, track token usage, debug tool calls, and monitor agent performance.
Standardizes Vitest unit and integration testing workflows for TypeScript, enforcing 70% coverage, proper mocking, and CI/CD-ready verification patterns.
A rigorous TDD workflow agent that enforces test-first development, ensuring 80%+ code coverage across unit, integration, and E2E tests for features, bug fixes, and refactoring.
Advanced Gemini-powered web search plugin with smart caching, subagent context isolation, and automated query optimization.
Automates the creation of Betty Framework skills by scaffolding directory structures, generating YAML manifests, and handling registry registration.
Full-stack SDLC agent workflow managing the entire production lifecycle from intake and planning to automated testing, CI/CD, and infrastructure deployment using MCP tools.
Generate comprehensive instructions for AI agents to operate the Taskery local Kanban board, including CLI, API, and concurrency management.