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Found 1,134 Skills
agent-team: Reset blocked, in-progress, or failed work to pending.
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.
Run adversarial review on a PM artifact via the pm-critic sub-agent. Dispatches natively on Claude Code with the pm-skills plugin (invokes @agent-pm-critic); on non-Claude clients (Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI) reads subagents/pm-critic.md and executes the system prompt inline. Returns findings graded P0/P1/P2/P3 with concrete fix suggestions per finding, plus a layered Status Summary section and machine-readable Status YAML block per master plan D26.
Run a repo-wide cross-cutting governance audit via the pm-skill-auditor sub-agent. Dispatches natively on Claude Code with the pm-skills plugin (invokes @agent-pm-skill-auditor); on non-Claude clients (Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI) reads subagents/pm-skill-auditor.md and executes the system prompt inline. Returns a layered audit report (full findings + Status Summary prose + Status YAML envelope per master plan D26) with cross-cutting findings graded P0/P1/P2/P3 plus aggregate counter audit and validator results table.
Walk the guided release runbook (6 gates G0/G1/G2/G2.5/G3/G4) via the pm-release-conductor sub-agent. Dispatches natively on Claude Code with the pm-skills plugin (invokes @agent-pm-release-conductor with native chain composition to pm-skill-auditor at G0 and pm-changelog-curator at G2); on non-Claude clients (Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI) reads subagents/pm-release-conductor.md and inlines auditor + curator behaviors at G0 + G2 via reference-and-execute-inline pattern (because non-Claude clients cannot natively chain to other sub-agents). Returns gate-by-gate output with explicit confirmation pauses, refuses bypass attempts, tags only the G2.5-captured SHA per master plan D22.
Reference and consulting skill for OpenClaw — a messaging gateway that connects AI agents to multiple communication platforms (Telegram, Discord, Slack, WhatsApp, iMessage, and more). Use when working with OpenClaw configuration, channels, Gateway setup, skills, cron jobs, MCP servers, memory, OAuth, or troubleshooting. Also use when the user asks how to implement a use case on their OpenClaw bot (daily morning brief, research workflows, competitive radar, decision playbook), how to add a new channel, or how to connect the CodeAlive context engine. Triggers on requests like "configure openclaw", "add Discord to my bot", "set up morning brief", "gateway not starting", "connect CodeAlive search", "OAuth re-auth", or any close paraphrase. Companion of install-openclaw-to-yc — install both together.
Paper Analyst — Responsible for in-depth paper reading, extracting method details, and building comparison tables. Activated when assigned to analyze papers by research supervisors or literature investigators. Conduct structured analysis on the Top 20 core papers, generate paper analysis cards and cross-paper comparison tables.
Create and configure AI agents, upload files for RAG, manage MCP servers, and handle agent memories using the Cargo CLI. Use when the user wants to create or update agents, upload knowledge base files, connect MCP tool servers, or manage agent memories. For sending messages to agents, use the cargo-orchestration skill instead.
Guide for adding a new benchmark or training environment to NeMo-Gym. Use when the user asks to add, create, or integrate a benchmark, evaluation, training environment, or resources server into NeMo-Gym. Also use when wrapping an existing 3rd-party benchmark library. Covers the full workflow: data preparation, resources server implementation, agent wiring, YAML config, testing, and reward profiling (baselining). Triggered by: "add benchmark", "new resources server", "integrate benchmark", "wrap benchmark", "add training environment", "add eval".
Give AI agents eyes into React apps - inspect component trees, props, state, hooks, and profile rendering performance from the command line
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.
Use this skill when the agent needs to interact with CLAWLOGIC prediction markets. This includes: registering as an agent on-chain, creating new prediction markets, analyzing market questions to form opinions, buying YES/NO positions, asserting market outcomes via UMA Optimistic Oracle, disputing incorrect assertions from other agents, settling resolved markets to claim winnings, and posting bet narratives ("what I bet and why") to the frontend feed. Triggers: - "create a market about..." - "what do you think about [market question]?" - "buy YES/NO on market..." - "assert the outcome of market..." - "dispute the assertion on market..." - "check my positions" - "settle market..." - Any discussion about prediction markets, trading, or information markets