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Found 2,368 Skills
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.
Use when a developer wants to build their first CopilotKit Channels agent and get it answering in Slack or Microsoft Teams — "set up a channel", "connect my agent to Slack", "get my agent into Teams", or starting from nothing and wanting a working channel end to end. Covers the whole path: inspecting or scaffolding the project, building the AG-UI agent, creating and reconciling the managed Channel with the public CopilotKit CLI, running the long-running host, and proving a real provider mention gets a reply. The workflow is not in this file — it is fetched from https://copilotkit.ai/channels-guide.md at run time, so it cannot go stale against the CLI.
Gate 0 research phase for pre-dev workflow. Dispatches 4 parallel research agents to gather codebase patterns, external best practices, framework documentation, and UX/product research BEFORE creating PRD/TRD. Outputs research.md with file:line references and user research findings.
Concurrent investigation pattern - dispatches multiple AI agents to investigate and fix independent problems simultaneously.
WeCom (Enterprise WeChat) CLI - official open-source CLI tool from WeCom. Covers 7 business categories: Contacts, Todos, Meetings, Messages, Schedules, Documents, Smartsheets. Built in Rust for macOS/Linux/Windows. Use when user wants to operate WeCom resources.
DingTalk Workspace CLI (dws) - officially open-sourced cross-platform CLI tool from DingTalk. Provides 86 commands across 12 products: Contact, Chat, Bot, Calendar, Todo, Approval, Attendance, Ding, Report, AITable, Workbench, DevDoc. Built in Go with zero-trust security architecture. Use when user wants to operate DingTalk resources.
Feishu/Lark CLI - official open-source CLI tool from Feishu for AI Agents. Provides 200+ commands across 12 business domains: IM, Docs, Sheets, Base (Bitable), Calendar, Video Meeting, Mail, Tasks, Wiki, Drive, Contacts, Search. Supports both user identity and bot identity authentication. Use when user wants to operate Feishu/Lark resources.
The social network for AI agents. Post, comment, upvote, and create communities.
Baidu Web Search skill for real-time Chinese web information retrieval. Breaks through static knowledge base limitations to get the latest news and information. Use when user needs to search the Chinese web for current information.
Create New Skill - scaffolds a skill definition following Claude Code conventions and this repository's patterns. Use when adding a new skill.
Generate or update project memory for AI agents — default to AGENTS.md, support agent-specific targets such as CLAUDE.md, and keep sibling memory files synchronized while capturing stable architecture, conventions, and operational knowledge
The full lifecycle for agentic loops — recurring, scheduled AI agents packaged as a portable LOOP.md (the agenticloops.dev standard: a trigger + skills + a prompt in one file any harness can install and run on a schedule). Use this whenever the user wants to FIND, INSTALL, RUN, or BUILD a loop: "find a loop for X", "is there a loop that…", "install a recurring agent that does X", "run this loop", as well as "create a loop", "make an agentic loop", "write a LOOP.md", "turn this into a recurring agent", "schedule an agent", "set up a cron job for an agent", or any description of a repeating job they want an agent to do on a timer (a daily digest, a competitor watcher, a triage sweep, a report pipeline, "email me X every morning", "check Y every hour") — even if they never say the word "loop". Always search the directory first and install an existing loop when one fits; author a new LOOP.md only when nothing does. This is the loop-level analogue of skill-creator + find-skills combined. For an ad-hoc in-session multi-agent run (spawn, verify, panel, fan-out) use the `loops` skill instead; for authoring a reusable SKILL.md use skill-creator.