Loading...
Loading...
Found 2,224 Skills
Single-pass feature implementation using Explore → Code → Test. Ships focused changes at maximum speed, with a built-in circuit breaker that stops and recommends `/apex` or `/forge` when the task turns out more complex than it looked. Use this whenever the user wants a quick win on a single, focused task — even when they don't say "oneshot" (e.g. "just", "quickly", "small change", "#42", or a GitHub issue URL for a small fix).
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
Configure, extend, or contribute to Hermes Agent.
Use when a Hermes Kanban worker wants to run Codex CLI as an isolated implementation lane while Hermes keeps ownership of task lifecycle, reconciliation, testing, and handoff.
MCP client: connect servers, register tools (stdio/HTTP).
Use when the user asks "what predefined metrics are available", "which built-in metrics should I use", "what does CSAT measure", "how does hallucination detection work", "what's the difference between Interruption Score and AI Interrupting User", "which metrics are free", "which metrics need audio", "configure silence threshold", "set up sentiment metric", or any question about Cekura's out-of-the-box metrics. Covers the full catalog of predefined metrics — what each does, costs, constraints, configuration options, and when to use each one.
Search Twitter for trending promotional posts related to coding/AI agent tools, generate reply drafts with the pikiclaw GitHub card, and push the results to Feishu Doc along with bot notifications. Does NOT auto-post to Twitter.
INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and which skill to load next.
Route users to OKX.AI customer support / Help Center. Use when the user wants to contact support, talk to a human, file a complaint, give feedback, report a system error or bug, or find the FAQ / help docs. Triggers: 'contact support', 'talk to a human', 'customer service', 'file a complaint', 'give feedback', 'help center', 'FAQ', 'user guide', 'system error', 'system bug', 'something is broken', 'find help docs', 'OKX AI support', 'OnchainOS support', 'human agent'.
Declared architecture snapshot for one Agentforce agent: planner, topics, actions, flows, Apex, prompt templates, and NGA plugins. Renders a human-readable architecture document and Mermaid invocation graph from design-time metadata (not runtime audit rows). TRIGGER when user asks to describe, diagram, inventory, audit, document, or diff (e.g. v3 vs v5) the architecture / action tree / topic structure / tool inventory of a specific agent by agent API name in a specific org. DO NOT TRIGGER for runtime session traces, conversation transcripts, generation timings, or gateway audit chains — this skill reads design-time metadata only (use investigating-agentforce-d360 for session traces).
Prevent feature creep when building software, apps, and AI-powered products. Use this skill when planning features, reviewing scope, building MVPs, managing backlogs, or when a user says "just one more feature." Helps developers and AI agents stay focused, ship faster, and avoid bloated products.
Set up automated agent-driven development with Ralph. Run AI agents in a loop to implement features from user stories, verify acceptance criteria, and log progress for the next agent.