Total 50,652 skills, AI & Machine Learning has 8490 skills
Showing 12 of 8490 skills
Query MiniMax API usage status. Triggered when users ask about MiniMax usage, quota, or consumption statistics. Display used quota, weekly limit, reset time, and Token consumption statistics; do not display model quota.
Apply Benjamin Graham's value investing framework to evaluate stocks, portfolio allocation, and investment vs. speculation decisions. Trigger on: "Is this stock worth buying?", "Is this investment or speculation?", "How should I allocate my portfolio?", "Is this company a good value?", "should I sell in a downturn?", "evaluate this stock for a defensive investor".
Expert media production assistant. Use when requested to help with storyboarding, podcast creation, audio assembly, or complex multi-step media workflows using the GenMedia MCP servers (Veo, Lyria, Gemini TTS, NanoBanana).
Remove background noise and isolate vocals/speech from audio using ElevenLabs Voice Isolator (audio isolation) API. Use when cleaning up noisy recordings, removing music or background ambience from dialogue, isolating speech from field recordings, preparing audio for transcription, extracting vocals, or any "denoise / clean up / isolate voice" task.
Framework for collective skill evolution in multi-user LLM agent ecosystems — automatically distills session experience into reusable SKILL.md files and shares them across agent clusters.
OpenAI Privacy Filter — bidirectional token-classification model for PII detection and masking in text
The root entry of the CodeStable workflow family — introduces the overall system to users and routes users' specific requests to the correct cs-* sub-skills. Trigger scenarios: users only input `cs` / `/cs`, say "introduce codestable", "do something with codestable", "I want to do X, which skill should I use", "don't know which one to use", or users' described requests are open-ended (e.g., "start working") and haven't converged to a specific sub-skill. This skill itself **does not perform actual tasks** — it doesn't write specs, write code, or read/write content products in the codestable/ directory — it only performs scanning, routing, prompting, and then transfers control to the target sub-skill.
End-to-end deep research and analysis pipeline. Takes a raw idea or market question, conducts deep web research, builds a competitive landscape, runs multi-framework intelligence analysis (/think), stress-tests it (/red-team), researches the red team findings, re-thinks with adversarial data, re-red-teams, and iterates until divergence between think and red-team is low (conviction stabilizes). Then generates a comprehensive single-file HTML report with all findings: market landscape, competitive analysis, intelligence briefs, red team results, how to win, and how you could lose. Use when the user says "/deepthink", "deep think", "deep research", or wants a comprehensive research-to-report pipeline on any idea, market, or strategic question.
Generative ideation engine. Takes a domain, trend, question, or constraint and produces 15-30 novel possibilities — things that might be true, businesses that could exist, futures that could unfold. Spawns a team of 6 specialist agents — Signal Scout, Analogist, Inverter, Combinator, Contrarian, Futurist — who each generate ideas from a distinct creative angle. The lead cross-pollinates across agents, finds unexpected combinations, and ranks the output by novelty × plausibility. Use when the user says "brainstorm", "what could exist", "what's possible", "generate ideas", "what might be true", "possibilities", or presents a domain and wants divergent exploration rather than evaluation of a specific idea.
Expert guidance for building conversational AI applications with Chainlit framework in Python. Use when (1) creating chat interfaces for LLM applications, (2) building apps with OpenAI, LangChain, LlamaIndex, or Mistral AI, (3) implementing streaming responses, (4) adding UI elements like images, files, charts, (5) handling user file uploads, (6) implementing authentication (OAuth, password), (7) creating multi-step workflows with visible steps, (8) building RAG applications with document upload, or (9) deploying chat apps to web, Slack, Discord, or Teams.
A methodology for iteratively improving agent-facing text instructions (skills / slash commands / task prompts / CLAUDE.md sections / code-generation prompts) by having a bias-free executor actually run them and evaluating two-sidedly (executor self-report + instruction-side metrics). Keep iterating until improvements plateau. Use it right after creating or substantially revising a prompt or skill, or when you want to attribute an agent's unexpected behavior to ambiguity on the instruction side.
Observe.AI platform help — enterprise contact center intelligence with Auto QA scoring on 100% of interactions, Agent Copilot real-time guidance, Coaching Copilot post-call performance management, VoiceAI and ChatAI virtual agents, screen recording, Insights Copilot. Use when setting up Observe.AI Auto QA scorecards for contact center agents, Agent Copilot not surfacing guidance during live calls, transcription accuracy issues or speaker attribution errors, comparing Observe.AI vs Balto or Cresta or CallMiner for contact center QA, integrating Observe.AI with Five9 or Amazon Connect or Talkdesk, or configuring compliance monitoring and regulatory audit trails. Do NOT use for building a general coaching program (use /sales-coaching) or reviewing a specific call transcript (use /sales-call-review).