LLM & Agents

Claude Code AI-assisted development workflow. Activate when discussing Claude Code usage, AI-assisted coding, prompting strategies, or Claude Code-specific patterns.

Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.

Use when testing web applications with AI-assisted Playwright. Features autonomous test agents for planning, generating, and self-healing tests automatically.

Writing Datasette plugins using Python and the pluggy plugin system. Use when Claude needs to: (1) Create a new Datasette plugin, (2) Implement plugin hooks like prepare_connection, register_routes, render_cell, etc., (3) Add custom SQL functions, (4) Create custom output renderers, (5) Add authentication or permissions logic, (6) Extend Datasette's UI with menus, actions, or templates, (7) Package a plugin for distribution on PyPI

Execution-layer skill for spawning subagents via runAgent

Guides optimal Linear operations usage with caching, performance patterns, and error handling. Auto-activates when implementing CCPM commands that interact with Linear. Prevents usage of non-existent Linear MCP tools.

Reviews Go test code for proper table-driven tests, assertions, and coverage patterns. Use when reviewing *_test.go files.

Vitest testing framework patterns and best practices. Use when writing unit tests, integration tests, configuring vitest.config, mocking with vi.mock/vi.fn, using snapshots, or setting up test coverage. Triggers on describe, it, expect, vi.mock, vi.fn, beforeEach, afterEach, vitest.

Dependency-aware issue tracking with bd. Use for managing tasks, bugs, and features with automatic dependency tracking, ready work detection, and AI agent integration. Perfect for tracking work that needs to be coordinated across multiple agents or tracking blockers and dependencies.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Use when implementing vector search with PostgreSQL. Covers PGVector hybrid search with BM25, metadata filtering, and performance optimization for semantic retrieval.

LLM content governance and compliance standards. Use when llm governance guidance is required.

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

Use when adding observability to LLM applications with Langfuse. Covers tracing, evaluation, prompt management, and cost tracking for self-hosted deployments.

Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.

Validate test coverage meets minimum thresholds for overall, statement, branch, and function coverage

A skill for automating AI CLI tool interactions by handling common prompts and managing continuous operation.

Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.

Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or reviewing for agent-introduced cruft.

Use when conducting web research with Perplexity API - covers authentication, search strategies, structured output generation, and integration patterns for Claude-interpretable results