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Found 1,463 Skills
This skill should be used when the user asks to "research a topic", "run-research", "last30", "what's happening with X", "what are people saying about X", "find the best X", "X prompts", "latest on X", "X news", "what are people recommending for X", "research X for me", or wants to know what's trending, discussed, or debated about any subject in recent weeks.
Persistent memory system for Claude Code. Two-layer architecture (hot cache + knowledge wiki), safety hooks, /close-day end-of-day synthesis. Zero external dependencies.
LLM-first SEO analysis skill with 16 sub-skills, 10 specialist agents, and 89 evidence collection scripts for comprehensive SEO audits
Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness — currently Code Mode, which collapses many tool calls into one sandboxed Python execution. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or tool sandboxing, when they want an agent to run agent-written Python, or when a Pydantic AI agent would benefit from orchestrating multiple tool calls in a single sandboxed script.
Use this skill when the user wants to analyze an existing pipe for improvement opportunities — automation gaps, manual bottlenecks, missing AI agents, field conditions, or adjacent processes. Acts as a process analyst: investigates, diagnoses, and improves the pipe in progressive rounds — each round delivers visible results.
Use for the PROVIDER half of getting a locally running CopilotKit Channels agent to answer in Slack, when no Slack app exists yet — setting up a Channels bot in Slack for the first time, creating the Slack app and its tokens, attaching it to a managed Intelligence Channel, or when a Channel reports setup_required, sits at "Waiting for runtime", the Channel is Online but a Slack mention gets no reply, or a Slack app was built with Socket Mode instead of an Intelligence Request URL. Scoped to an OpenTag checkout, or the OpenTag example inside a channels-sdk clone — the phases assume those conventions (app/channel.tsx, app/env.ts, INTELLIGENCE_CHANNEL_NAME, a local agent on port 8123) and do not describe a project scaffolded by copilotkit init, which already ships its own channel host. If the Slack app and Channel already exist and the question is about declaring or customising the Channel in code, use the copilotkit-channels skill instead.
Audit and reduce AI agent runtime spend in dollars. Use for AI costs, agent spend, token waste, runtime attribution, detector coverage, and FinOps. Works with OpenClaw, Hermes, QM, Claude Code, Cursor, and generic event ingest.
Use xurl to access AI agent conversations via agents:// URIs. Invoke when the user: gives an agents:// URI, a provider shorthand like provider/..., or a bare thread/session ID; mentions conversations, threads, or sessions from any AI coding agent; wants to search, read, summarize, compare, or continue agent threads; asks what they worked on, what an agent said, or references past agent interactions; wants to delegate work to or start a conversation in another agent.
Set up state-of-the-art context engineering for any repository. Analyzes codebase, generates multi-level CLAUDE.md/AGENTS.md hierarchy, hooks, session management, and token budgets. Based on 200+ sources including ETH Zurich, Anthropic, Google DeepMind, and Manus production data. For engineers who ship with AI agents.
Meta-router for the workflow recipes in ~/.claude/workflows/ (personal layer) and the current repo's .claude/workflows/ (shadows personal on name collision). Invoke before any loop-shaped work — audits, consensus gates, plan→build lifecycles, findings triage. Even a 1% chance this applies means invoke it.
Guide developers through creating a Slack app or agent using the Slack CLI and Bolt (JS or Python). Handles prerequisites, sandbox setup, authentication, project creation from templates, and local development.
Autonomous execution workflow for complex long-running tasks. This applies to scenarios where users have a complex or vague task (e.g., "Help me figure out X / Help me evaluate Y / Help me organize this pile of stuff / Help me compare N solutions / Help me run a research"), and expect the AI to decompose, execute, and verify the task on its own, only reaching out to the user at critical moments. It enables unattended autonomous execution for 1-2 hours through the process of "Task Confirmation → Task Queue → Batch Execution → Periodic Queue Verification → Triggered Reporting". It is triggered when users say phrases like "Help me figure out / Evaluate / Organize / Compare / Run a research / Run it on your own don't bother me / Long-running task / Run autonomously". **Not applicable to**: UI design (use design-exploration), to-do priority judgment (use priority-judge), article writing (use writing-assistant), backlog management (use backlog-manager), vision exploration (use vision-exploration), naming (use product-naming), implementation coding tasks with clear specs (code directly).