spawn-agent
Spawn PAI agents via MCP factory tool. Loads identity, injects RAG context, validates spawn chain, and executes via Task(). The bridge between MCP tools and Claude Code's agent spawning.
Spawn PAI agents via MCP factory tool. Loads identity, injects RAG context, validates spawn chain, and executes via Task(). The bridge between MCP tools and Claude Code's agent spawning.
Workflow patterns and gotchas for Anthropic/Claude agents. Directs to RAG for implementation.
Use when saving current iteration progress mid-conversation, before context compaction, or at interim pause points
Hypothesis-driven debugging with hybrid dual-track parallel execution (Opus 4.5 + GPT 5.2). Spawns two independent chains of subagents where each reviews and improves upon its own previous work, then synthesizes findings from both tracks. Use when debugging hard-to-reproduce bugs, CI/E2E test failures, flaky tests, or when standard fixes have failed.
Use when creating custom Claude Code subagents - guides YAML frontmatter structure, system prompts, tool restrictions, model selection, and permission configuration
Claude Code settings management, preference customization, and user experience optimization. Use when customizing Claude Code behavior, managing user preferences, or optimizing development experience.
Master context engineering for AI agents - token optimization, degradation patterns, compression, memory systems, multi-agent coordination, evaluation. Use when designing agents, debugging context failures, or building LLM pipelines.
Use when explicitly asked to run the code-reviewer subagent or when another skill requires the code-reviewer agent card.
Creates PhD-grade expert agents when no suitable agent exists. Produces highly specialized agents with deep domain expertise.
LLM observability with self-hosted Langfuse 3.x - tracing, evaluation, monitoring, prompt management, and cost tracking
Navigate skill graphs via deterministic random walks. Fuses derivational chains, algebraic structure, color determinism, and bidirectional flow for skill recombination.
When orchestrating tasks, load this core skill first to understand the general methodology.
Ensures proper use of PAL MCP tools (thinkdeep, debug, codereview, consensus, planner) for complex tasks requiring deep analysis, multi-model collaboration, or systematic investigation. Auto-activates when: - User requests debugging, code review, or planning assistance - Complex problems require systematic investigation - Multi-model consensus needed for architectural decisions - Deep thinking required for root cause analysis Provides guidance on: - When to use each PAL MCP tool - Proper continuation_id management - Model selection strategies - Workflow orchestration patterns
ElevenLabs voice cloning techniques, audio quality requirements, recording best practices, and training data optimization for professional-quality voice clones. Use when creating custom voices, cloning voices, or optimizing voice clone quality.
Use when instruction files (skills, prompts, CLAUDE.md) are too long or need token reduction while preserving capability. Triggers: "optimize instructions", "reduce tokens", "compress skill", "make this shorter", "too verbose".
Metaskill that fans out on every interaction, using interaction entropy
Enterprise-grade Context7 MCP integration patterns for language-specific documentation access with real-time library resolution and intelligent caching
Guide for creating custom agents for Claude Code with specialized behaviors and tools
Creates or updates skills with proper YAML frontmatter, progressive disclosure, and best practices per the open Agent Skills specification. Supports simple, tool-restricted, multi-file, and script-based skills. Use when creating new skills, authoring skills, extending agent capabilities, or when `--create-skill` or `--new-skill` flag is mentioned.
Use when preparing to fine-tune an LLM for multi-turn conversations, before generating any training data. Triggers - starting a fine-tuning project, need to define evaluation criteria, designing conversation data generation.
This skill should be used when users need to scrape websites, extract structured data, handle JavaScript-heavy pages, crawl multiple URLs, or build automated web data pipelines. Includes optimized extraction patterns with schema generation for efficient, LLM-free extraction.