Total 55,561 skills, AI & Machine Learning has 9241 skills
Showing 12 of 9241 skills
Expert skill for building AI systems with Weft, a Rust-based programming language where LLMs, humans, APIs, and infrastructure are first-class primitives with typed connections and durable execution.
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.
Generate images using Minimax image-01, triggered when the user says "Generate images with Minimax".
Use Alibaba Cloud DashScope API and LingMou to generate AI video and speech. Seven capabilities — (1) LivePortrait talking-head (image + audio → video, two-step), (2) EMO talking-head, (3) AA/AnimateAnyone full-body animation (three-step), (4) T2I text-to-image (Wan 2.x, default wan2.2-t2i-flash), (5) I2V image-to-video (Wan 2.x, default wan2.7-i2v-flash, supports T2I→I2V pipeline), (6) Qwen TTS (auto model/voice by scene, default qwen3-tts-vd-realtime-2026-01-15), (7) LingMou digital-human template video with random template, public-template copy, and script confirmation. Trigger when the user needs talking-head, portrait, full-body animation, text-to-image, text-to-video, or speech synthesis.
Image Generation Skill: Use this skill when users need to generate images, visual infographics, create graphics, or edit/modify/adjust existing images. Based on the official formal version of the ChatGPT Image 2 model (gpt-image-2) from Apiyi Platform (https://api.apiyi.com/). This model supports precise size/quality control (including 4K) and is billed by token. Key differences from gpt-image-2-all (official reverse version): Uses /v1/images/generations and /v1/images/edits endpoints; Has explicit size parameter; Has quality parameter; Billed by token; Uses multipart/form-data to upload reference images; b64_json is pure base64 without prefix.
Use this skill to turn a raw user request into a structured, model-agnostic task brief before execution, and — when the brief survives confirmation — to be the sole entry point that creates a task directory at `.agents/tasks/<task-id>/`. Invoke whenever the request is complex, multi-step, cross-domain, ambiguous, or will be handed off to another model or agent. Also trigger when the user says things like 'help me figure out what I need', 'I'm not sure how to ask this', 'I want to do X but I don't know where to start', 'take this and make it clearer', or when the task mixes multiple goals or domains. Do NOT trigger for simple one-line requests with clear intent (e.g., 'fix the typo on line 42', 'rename this variable').
Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, meta-judge → LLM-as-a-judge verification
Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with meta-judge evaluation specifications and multi-agent evaluation
Create a workflow command that orchestrates multi-step execution through sub-agents with file-based task prompts
Generate ideas in one shot using creative sampling
Generate seamless, tileable patterns using each::sense AI. Create repeating patterns for textiles, wallpapers, gift wrap, digital backgrounds, and surface designs that tile perfectly without visible seams.
Generate print-ready t-shirt and apparel designs using each::sense AI. Create graphic tees, typography designs, vintage styles, illustrations, and more for custom apparel printing.