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Context tracking and decision logging patterns for intentional memory management in Claude Code Waypoint Plugin. Use when you need to remember user preferences, track decisions, capture context across sessions, learn from corrections, or maintain project-specific knowledge. Covers when to persist context, how to track decisions, context boundaries, storage mechanisms, and memory refresh strategies.
Scans for project documentation files (AGENTS.md, CLAUDE.md, GEMINI.md, COPILOT.md, CURSOR.md, WARP.md, and 15+ other formats) and synthesizes guidance. Auto-activates when user asks to review, understand, or explore a codebase, when starting work in a new project, when asking about conventions or agents, or when documentation context would help. Can consolidate multiple platform docs into unified AGENTS.md.
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.
Generic MCP (Model Context Protocol) server development patterns. Provides reusable architecture and best practices for building MCP servers that expose any domain-specific operations as tools for AI agents. Framework-agnostic implementation supporting async operations, error handling, and enterprise-grade features.
Enhanced code search with semantic understanding, pattern matching, and intelligent query interpr...
Spawns multiple AI coding agents to work on related GitHub issues concurrently using git worktrees. Use when breaking down a large feature into multiple issues, running parallel agents with --print flag, or managing wave-based execution of related tasks.
Expert at creating and modifying Claude Code agents (subagents). Auto-invokes when the user wants to create, update, modify, enhance, validate, or standardize agents, or when modifying agent YAML frontmatter fields (especially 'model', 'tools', 'description'), needs help designing agent architecture, or wants to understand agent capabilities. Also auto-invokes proactively when Claude is about to write agent files (*/agents/*.md), create modular agent architectures, or implement tasks that involve creating agent components.
Automatically activated when user asks to "find patterns in...", "identify repeated code...", "analyze the architecture...", "what design patterns are used...", or needs to understand code organization, recurring structures, or architectural decisions
Analyzes narrative plot points, timelines, and story events to identify inconsistencies, plot holes, continuity errors, and pacing issues. Use when the user needs help ensuring their story remains logically consistent and well-paced.
Expert at performing task X automatically. Auto-invokes when the user wants to do Y, needs help with Z, or encounters situation W.
Invoke external AI CLIs via native Task agents (Claude, Codex, Gemini, Cursor). Primary mode for multi-provider orchestration with fork-terminal fallback for auth.
Use this skill for requests related to Pydantic AI framework - building agents, tools, dependencies, structured outputs, and model integrations.
Creates Claude Code skills where each skill is tied to a specialist agent optimized with evidence-based prompting techniques. Use this skill when users need to create reusable skills that leverage specialized agents for consistent high-quality performance. The skill ensures that each created skill spawns an appropriately crafted agent that communicates effectively with the parent Claude Code instance using best practices.
Meta-skill enforcing skill discovery and invocation discipline through mandatory workflows. Use when starting any conversation to check for relevant skills before any response, ensuring skill-first workflow before proceeding.
Fetch current model names from AI providers (Anthropic, OpenAI, Gemini, Ollama), classify them into tiers (fast/default/heavy), and detect new models. Use when needing up-to-date model IDs for API calls or when other skills reference model names.
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.
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.
