python-ml-workflow
Expert guidelines for Python ML and LLM workflows. Covers code quality, experiment tracking, and data handling. Use when working on AI/ML components or data pipelines.
Find developer tool skills for Claude Code, Cursor, and other AI agents. Automate coding, debugging, refactoring, and project workflows.
This directory brings installable AI Agent skills into one place so you can filter by search, category, topic, and official source, then install them directly into Claude Code, Cursor, Windsurf, and other supported environments.
Expert guidelines for Python ML and LLM workflows. Covers code quality, experiment tracking, and data handling. Use when working on AI/ML components or data pipelines.
Automates the creation of strict PHPUnit tests. It specializes in mocking Repositories/Configs using `Mockery` and validating `App\Core\ServiceResponse` objects. It ensures no feature is considered complete without a test. Use this skill when a new **Service Method** is created or a bug is reported.
Execute a single Ralph development cycle by selecting a failing task, implementing it, verifying with tests, and committing. Use when ready to implement the next feature from the backlog.
Use Nia MCP server for external documentation, GitHub repos, package source code, and research. Invoke when needing to index/search remote codebases, fetch library docs, explore packages, or do web research.
Code quality pillars, goals, abstraction layers, and tradeoff thinking. Use when evaluating code quality, setting quality goals, choosing abstraction levels, making design tradeoffs, or auditing code against quality pillars. Covers readability, modularity, testability, reusability, and the principle of least astonishment.
📖 My knowledge Wiki by scraps (https://github.com/boykush/scraps)
Pinia store TypeScript configuration and typing issues. Covers storeToRefs type loss, getters circular references, and setup store patterns. Use when working with Pinia stores in Vue 3 projects, debugging store type errors, or fixing storeToRefs type inference.
Python 3.11+ performance optimization guidelines (formerly python-311). This skill should be used when writing, reviewing, or refactoring Python code to ensure optimal performance patterns. Triggers on tasks involving asyncio, data structures, memory management, concurrency, loops, strings, or Python idioms.
Use these tools to ensure all code meets the projects architectural and quality standards before considering a task complete.
Work a GitHub issue -- validate, test, plan, implement, report
Provide implementation patterns and runnable examples for the Temporal Rust SDK prototype. Use when building, migrating, or debugging Temporal applications in Rust, including Workflow and Activity authoring, Worker and Client wiring, Signal handling, Local Activities, Saga compensation, and activity registration strategies.
Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in.