Total 50,320 skills, AI & Machine Learning has 8453 skills
Showing 12 of 8453 skills
Richard Feynman's Integrity Audit applied to any analysis, business plan, or decision. Spawns a team of specialist agents — Source Auditor, Self-Deception Hunter, Translation Tester, Cargo Cult Inspector, Confidence Inverter — who each apply a distinct lens from Feynman's framework to detect dishonesty, self-deception, and cargo cult reasoning. The lead synthesizes into a verdict: is this analysis honest, or is it fooling itself? Use when the user says "feynman this", "integrity audit", "is this honest", "am I fooling myself", "cargo cult check", or wants to stress-test any analysis, plan, or claim before trusting it. Works standalone or as a meta-audit after /munger or /thiel.
CallMiner platform help — enterprise conversation analytics (Eureka) with omnichannel interaction capture, automated QA scoring, agent coaching, real-time alerts, compliance monitoring, and CX automation. Use when QA scoring is inconsistent or takes too long across agents, when needing to analyze 100% of customer interactions instead of sampling, when setting up automated compliance monitoring for regulated industries (healthcare, finance, collections), when CallMiner Coach scorecards aren't surfacing the right coaching moments, when CallMiner RealTime alerts aren't triggering during live calls, when ingesting audio or text into CallMiner via the Ingestion API, when CallMiner Analyze categories aren't matching expected interactions, or when evaluating CallMiner vs Observe.AI or NICE CXone analytics. Do NOT use for CCaaS platform selection (use /sales-ccaas-selection) or for sales-specific coaching strategy (use /sales-coaching).
Supernormal platform help — AI agent for agencies that turns meeting context into deliverables (pitch decks, briefs, emails, spreadsheets). Use when setting up Supernormal desktop app for bot-free recording, Supernormal AI agents not generating deliverables, Supernormal credits running out or credit system confusion, Supernormal bot joining Zoom calls uninvited, comparing Supernormal to Sembly or Fathom or Fireflies for agency work, Supernormal MCP integration, Supernormal Slack or CRM sync to HubSpot or Salesforce, or Supernormal transcription accuracy issues with accents. Do NOT use for choosing between AI note-takers (use /sales-note-taker) or general meeting transcript API integration (use /sales-note-taker).
Altern platform help — curated AI tools and agents directory (10,000+ tools, 100+ categories, ~5-28K monthly visits). Covers tool submissions (free + featured tiers: Gold/Silver/Bronze), listing optimization, category selection, newsletter inclusion (weekly AI tools + agents digest), alternatives pages, and dofollow backlinks. Use when your AI tool isn't listed on Altern, listing isn't getting visibility, not sure if a featured tier is worth it, or wondering how Altern compares to other AI directories. Do NOT use for multi-directory launch coordination (use /sales-launch-directory). Do NOT use for non-AI product directories (use the platform-specific skill).
Help a CS or AI PhD student design hypothesis-driven experiments with baselines, variables, metrics, controls, logging, and stop conditions. Use this skill whenever the user is about to run experiments, compare models, plan an ablation, debug inconclusive results, prepare an experiment section, or wants to avoid changing too many things at once.
Help a CS or AI PhD student turn a rough research idea into a validated next-step decision using the handbook's FIVE+C framework. Use this skill whenever the user says they have a research idea, wants to know whether an idea is worth pursuing, needs help choosing between project directions, is preparing to pitch an idea to an advisor or senior student, or feels unsure whether a project is too incremental, too ambitious, already solved, hard to evaluate, or missing resources.
Audit a CS or AI research project for reproducibility across environment, data, code, configuration, logging, and documentation. Use this skill whenever the user wants to make experiments reproducible, prepare code for collaborators, debug environment drift, write a README, package a project for paper release, or ensure they can rerun results months later.
AI Image Generation Skill, using the latest ChatGPT image generation model gpt-image-2-all. This skill is applied when users need to generate images, visual infographics, create graphics, or edit/modify/adjust existing images. Based on the image generation service of the latest ChatGPT image generation model gpt-image-2-all from APIYI Platform (https://api.apiyi.com/), no external network access is required. The model is charged per image at $0.03 per piece, supporting text-to-image generation, single image editing, multi-image fusion, and natural language-based image modification, with high text restoration accuracy and friendly Chinese prompts. The size is controlled by prompt description (no explicit size parameter). Key differences from NanoBanana2: no size parameter, need to describe the size at the beginning of the prompt; unified $0.03 per image with no resolution tiering; the conversational endpoint /v1/chat/completions is the recommended one.
Generate educational comics from academic papers, explaining core viewpoints and innovations through visual storytelling. Supports 4 art styles: classic (clean line), tech (technical), warm (warm tone), chalk (chalkboard). Uses baoyu-gemini-web to generate images.
Dynamic, reflective problem-solving through structured sequential thoughts with support for branching, revision, and adaptive depth. Use this skill when: (1) Breaking down complex problems into steps, (2) Planning and design with room for revision, (3) Analysis that might need course correction, (4) Problems where the full scope is not clear initially, (5) Multi-step solutions requiring maintained context, (6) Situations where irrelevant information must be filtered out, (7) Any task benefiting from hypothesis generation, verification, and iterative refinement. Triggers: think through, step by step, break this down, sequential thinking, reason through, analyze step by step, think carefully, or when a problem clearly benefits from structured multi-step reasoning.
Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
Li — Knowledge Manager for Ane's library and MEL Wiki. Use when Ane needs to catalog, retrieve, or reorganize documents in the personal knowledge library, or query/maintain the MEL Wiki. Handles INGEST, QUERY, and LINT operations. Does not answer domain questions — retrieves and organizes knowledge for other agents and Ane.