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Found 6,586 Skills
Debug and trace C/C++/Rust programs with the GNU Debugger (GDB) without blocking the agent. Use when you need to set tracepoints, inspect variables, or monitor a running process while staying responsive to the user.
Clean code patterns for Azure AI Search Python SDK (azure-search-documents). Use when building search applications, creating/managing indexes, implementing agentic retrieval with knowledge bases, or working with vector/hybrid search. Covers SearchClient, SearchIndexClient, SearchIndexerClient, and KnowledgeBaseRetrievalClient.
Search-aware context compression workflow for agent-studio. Use pnpm hybrid search + token-saver compression, then persist distilled learnings via MemoryRecord.
Post-completion self-review for coding agents that runs simplify, harden, and micro-documentation passes on non-trivial code changes. Use when: a coding task is complete in a general agent session and you want a bounded quality and security sweep before signaling done. For CI pipeline execution, use simplify-and-harden-ci.
Monitor running agent loops, triage failures, clean up after completion, and decide when to intervene. Use when a loop is running and needs babysitting, when a loop just finished and needs post-merge verification, when stories are skipping/failing and need diagnosis, or when stale test artifacts need cleanup. Triggers on: 'check the loop', 'what happened with the loop', 'loop finished', 'clean up after loop', 'why did that story skip', 'monitor loop', 'nanny the loop', or any post-start loop management task. Distinct from agent-loop skill (which handles starting loops).
Interactive session to craft a system prompt for an AI agent powered by Sanity Agent Context MCP.
Trading personality and arena behavior for pump.fun token trading. Governs how the agent trades, announces trades, reacts to other agents, and handles wins and losses in the shared arena group.
Play blackjack with the agent as dealer. The agent manages game state, deals cards, and sends card images.
Multi-agent coordination discipline: one-message-then-wait (send complete context, wait for reply before sending again), idle notifications are heartbeats (no action unless extended + blocking + user asked), no polling loops (event-driven only), never fabricate agent responses (wait for real system events), sequential agent spawning (acknowledge between each), and proper shutdown protocol (request, wait, respect rejection). Activate when orchestrating multiple agents, managing agent teams, coordinating handoffs between agents, spawning subagents, or building multi-agent workflows. Triggers on: "coordinate agents", "spawn multiple agents", "manage agent team", "agent keeps sending messages", "polling loop", "agent idle", "shut down agent", "multi-agent workflow", "agent handoff", "coordinate parallel work", "stop bothering the other agent". Also relevant when an agent is fabricating responses, sending follow-up messages before replies arrive, or reacting to idle notifications unnecessarily.
Maintain /do routing tables and command references when skills or agents are added, modified, or removed. Use when skill/agent metadata changes, after skill-creator-engineer or agent-creator-engineer runs, or when routing tables need synchronization. Use for "update routes", "sync routing", "routing table", or "refresh /do". Do NOT use for creating new skills/agents, modifying skill logic, or manual /do table edits.
Use this skill when you need to operate the Creem CLI for authentication checks, products, customers, checkouts, subscriptions, transactions, configuration, monitoring, or terminal automation workflows. Prefer it for agent-driven Creem tasks that should use real CLI commands and JSON output instead of dashboard clicks or guessed API calls.
Deploy OpenClaw AI agent platform on Alibaba Cloud ECS and integrate with DingTalk bot. OpenClaw (formerly Clawdbot/Moltbot, 中文名"龙虾") is an open-source AI assistant and automation platform supporting natural language-driven task automation with multi-channel chat integration. This Skill covers the full workflow from ECS instance creation, public network configuration, base environment setup, one-click OpenClaw deployment to DingTalk bot verification. End users can chat with the AI assistant by @mentioning the bot in a DingTalk group. Triggers: "OpenClaw", "龙虾", "Clawdbot", "Moltbot", "DingTalk bot", "DingTalk AI", "deploy OpenClaw on ECS", "AI agent platform", "DingTalk integration", "openclaw dingtalk", "openclaw deploy", "DingTalk AI employee", "Alibaba Cloud OpenClaw", "Bailian + DingTalk", "DingTalk group AI", "DingTalk smart assistant", "部署龙虾", "龙虾机器人", "龙虾钉钉"