Total 50,680 skills, AI & Machine Learning has 8495 skills
Showing 12 of 8495 skills
Compress LLM responses to pure signal — Rocky's early notation style. Drop articles, filler, hedging. Best for pipelines and coding.
Multi-model agent orchestration using specialized agents for planning, coding, research, math/science, visual analysis, and adversarial review. Use when tasks are complex enough to benefit from different models' strengths, when you want adversarial review to catch blind spots, or when coordinating multi-step workflows across agent roles. Triggers on complex projects, multi-step tasks, architecture decisions, or when explicitly requested.
Discover session files for a repo across Claude Code, Codex, and Cursor, and extract session metadata (timestamps, branch, cwd, size, platform). Invoked by session-research agents — not intended for direct user queries.
Use when implementing ANY Apple Intelligence or on-device AI feature. Covers Foundation Models, @Generable, LanguageModelSession, structured output, Tool protocol, iOS 26 AI integration.
· Batch-improve skill collections with evaluation loops, lint checks, behavioral tests, peer review. Triggers: 'skill refiner', 'improve skills', 'quality sweep', 'batch improve', 'skill loop'. Not for one skill.
Ask questions and read documentation about any GitHub repository using DeepWiki MCP. Use when you need to understand a codebase, find specific APIs, or get context about a repository.
Scaffolds a complete agent TUI in TypeScript using @openrouter/agent — like create-react-app for terminal agents. Generates a customizable terminal interface with three input styles, four tool display modes, ASCII banners, streaming output, session persistence, and configurable tools. Use when building an agent, creating a TUI, scaffolding an agent project, or building a coding assistant.
Query OpenRouter for available AI models, pricing, capabilities, throughput, and provider performance. Use when the user asks about available OpenRouter models, model pricing, model context lengths, model capabilities, provider latency or uptime, throughput limits, supported parameters, wants to search/filter/compare models, or find the fastest provider for a model.
Nassim Taleb's Antifragility framework applied to a business idea, system, or portfolio position. Spawns a team of specialist agents — Fat-Tail Detector, Fragility Auditor, Optionality Scout, Iatrogenics Checker, Skin-in-the-Game Auditor — who each apply a distinct lens from Taleb's Incerto to evaluate whether the subject is fragile, robust, or antifragile. The lead synthesizes into a convexity assessment: what's the payoff structure under disorder, where are the hidden tail risks, and the honest Taleb verdict. Use when the user says "taleb this", "is this fragile", "antifragility analysis", "what would Taleb think", "tail risk check", or proposes a business/system and wants structural risk analysis. Works standalone or after /munger for complementary analysis.
Omi AI wearable platform help — open-source AI necklace for all-day conversation capture (in-person + online meetings), Developer API (`api.omi.me/v1/dev`, Bearer token, 100 req/min), app marketplace with webhook integrations, memories/conversations/action-items endpoints. Use when setting up an Omi wearable for meeting capture, building a custom Omi app or integration, troubleshooting Bluetooth disconnects or transcription accuracy, connecting Omi to Slack or CRM via webhooks, comparing Omi to Plaud or Limitless for in-person recording, or accessing Omi's API to export conversations and action items. Do NOT use for choosing between software-only note-takers without wearable needs (use /sales-note-taker).
Enthu.AI platform help — contact center conversation intelligence with auto QA scorecards, agent coaching, compliance monitoring, and speech analytics. Use when setting up Enthu.AI QA scorecards for call center agents, calls not being scored or transcribed correctly, agents not seeing coaching insights from their calls, Enthu.AI integration with Aircall or RingCentral not syncing, comparing Enthu.AI vs Gong or CallMiner for contact center QA, or configuring sentiment analysis and keyword tracking. Do NOT use for building a general coaching program (use /sales-coaching) or reviewing a specific call transcript (use /sales-call-review).
Evidence-based Drug-Drug Interaction (DDI) assessment skill modeled after the Micromedex Drug-Reax methodology. Trigger this skill whenever the user types /drug-drug, mentions "drug interaction", "DDI", "drug-drug", "can I take X with Y", "interaction between", "交互作用", "併用", or asks whether two medications can be used together. This skill performs systematic literature retrieval via PubMed, CrossRef, and WebSearch, then produces a structured assessment report with Severity, Documentation, Onset, Mechanism, Clinical Effects, and Management — mirroring the Micromedex Drug-Reax classification framework. Even casual questions like "is it safe to combine A and B" should trigger this skill.