LLM & Agents

Use when execute command encounters errors - diagnostic guide for phase failures, parallel agent failures, merge conflicts, worktree issues, and recovery strategies

Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.

Helps choose the right Claude Code extension mechanism (slash commands, skills, subagents, or hooks) for a given use case. Use when discussing how to extend Claude Code, automate workflows, or implement custom functionality.

GPT-5 prompting best practices for creating AI agent prompts in OpenPromo codebase when using ai sdk or agents, or in general writing llm prompts.

Design code for testability and AI/LLM ergonomics with explicit contracts and observable patterns. Use when optimizing code for AI tools, improving testability, or making codebases LLM-friendly.

This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.

Auto-loads when CLAUDE_CODE_TEAM_NAME environment variable is set. Provides guidance for Claude Code teammates working in swarms - identity awareness, communication patterns, task management, and coordination protocols. Use when you are a spawned teammate (not the team lead).

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.

Production hybrid search with PGVector + BM25 using Reciprocal Rank Fusion, 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.

LLM observability with self-hosted Langfuse - tracing, evaluation, monitoring, prompt management, and cost tracking

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

Building Expo DevTools Plugins with CLI Interfaces for interacting with running Expo apps using agents.

Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.