Total 50,615 skills, AI & Machine Learning has 8484 skills
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Cloudflare Workers AI for serverless GPU inference. Use for LLMs, text/image generation, embeddings, or encountering AI_ERROR, rate limits, token exceeded errors.
Generate a detailed AI image prompt for creating an attractive female UGC ad character. Use when the user wants to create a "hot girl" character image for UGC ads, influencer-style content, product testimonials, or social media ad creatives. Triggers on requests like "create a UGC girl", "hot girl for ads", "female influencer image", "UGC character", "testimonial girl", or any request for a female character for ad/UGC content.
Propose and execute rubric or bucket upgrades. Two modes: **Full rubric bump** (highest-risk action, mandatory 5-step process + cross-model audit) and **--bucket-only lightweight recalibration** (only update bucket boundaries, no changes to rubric formulas). **Phase 2 mandates using cheat-score-blind sub-agent to re-score the calibration pool** — self-scored fallback is not accepted. Trigger phrases: "upgrade rubric"/"bump rubric"/"update formula"/"I want to add a dimension"/"adjust weights"/"recalibrate bucket"/"recalibrate bucket".
Build and maintain a Karpathy-style LLM knowledge base — a self-compiling Obsidian markdown wiki where an Agent ingests raw sources, compiles cross-linked concept/entity/summary pages, answers queries against the corpus, lints the graph for health, and audits in-context human feedback filed from Obsidian or the local web viewer. Use when (1) scaffolding a new knowledge base for any research topic, (2) ingesting articles/papers/PDFs/web pages into raw/, (3) compiling or restructuring wiki articles from existing raw material, (4) answering questions against the wiki and filing durable answers back, (5) running lint passes for dead links / orphan pages / coverage gaps / audit shape, (6) processing human feedback from the audit/ directory and applying corrections. Not for general note-taking, daily journals, or non-wiki Obsidian use.
This skill is used when users want to add QQ platform support to the official main branch of Hermes Agent, or explicitly mention requests like "add QQ channel to hermes main", "install QQ support as a skill to Hermes", or "enable the official version of Hermes to support QQ and file sending". This skill will update the current repository to a version that supports QQ Bot, QQ file sending, QQ platform configuration, and toolset integration.
This skill should be used when the user asks to "repair an agent", "audit an agent", "fix my agent", "review agent quality", "check if my agent is well-written", "diagnose agent problems", "what's wrong with this agent", "improve this agent", or "what's wrong with this agent file". Not for skills — use repair-skill.
Multi-perspective deliberation on a question. Use when the user says "get perspectives on", "multiple viewpoints", "council on this", "devil's advocate", "stress test this idea", "red team this", "poke holes in", "second opinion on", "what am I missing", or wants multi-perspective analysis of a decision, design, or strategy.
Use when the user wants to iterate on a viral-article scoring system itself, calibrate or improve a scoring prompt against labeled samples, or run batch scoring experiments on a fixed article set. Best for prompt-only scoring research where the evaluator scripts stay fixed and only the scoring rubric/prompt is meant to evolve.
Especialista em pesquisa, análise de dados e gestão do conhecimento no SynkOS. Use esta skill quando o usuário pedir para pesquisar um tema, analisar dados ou evidências, consolidar conhecimento disperso, criar ou atualizar páginas de wiki, documentar achados de discovery, extrair padrões de múltiplas fontes, ou responder perguntas como "o que já sabemos sobre X?", "quais são os riscos de Y?", "pesquise Z e documente". Ative também para auditar a saúde do wiki, promover padrões para memória persistente, ou quando o contexto precisar ser levantado antes de uma decisão técnica ou de produto.
Design background Data Atlas style agents for Itô basket research, market discovery, parameter drafting, and human-in-the-loop editing. Use for architecture and workflow planning, not live order execution.
Scaffold the Mimas agent instruction file tree for any repository — AGENTS.md at root, subdomain CONTEXT.md files, and the full agents-docs/ hierarchy (a sibling of any existing docs/, kept separate so human-maintained project docs stay untouched). Every file is tailored to the repo's actual tech stack, git platform, and conventions. Use this skill whenever someone wants to set up agent instructions, onboard a repo for AI-assisted development, add AGENTS.md / CONTEXT.md files, create engineering docs for agents, or mentions "set up agentic repository" or "mimas template". Even if they just say "set up this repo for agents" or "add agent docs", this is the skill to use.
Write dense storyboard-grid prompts for short-form image or previsualization workflows. Use this when a generation controller needs a 6-9 panel grid with hook logic, visible actions, product timing, and negative constraints before image or video request architecture.