Total 50,892 skills, AI & Machine Learning has 8520 skills
Showing 12 of 8520 skills
Detect new or modified skills in .agents/skills/ by comparing git hashes against ai-skills, snapshot for rollback, review, publish to ai-skills, install locally, and cherry-pick lockfile to TARGET. Replaces /elevate-skill.
Standalone multi-agent image generation skill for Hermes. Includes an internal design compiler, GPT-Image-2 generation via apimart.ai, case library reuse, interactive reference selection, batch workflows, and style-consistent series generation.
Create an AI persona from scratch. Interactive guidance: Enter persona name → Provide materials (URL/file/pasted text) → Automatic distillation → Output a directly usable skill directory. Activate when: User says /create-soul, "创建人物", "蒸馏 [某人]", "create a persona for [name]".
Choose GPT-Image2 / gpt-image-2 visual styles and industrial prompt templates from the awesome-gpt-image-2 style library. Use when an agent needs to create, rewrite, classify, or improve image-generation prompts with repository-backed templates, categories, style tags, scene tags, pitfalls, and example cases.
Lossless LLM-optimized compression of source documents. Use when the user requests to 'distill documents' or 'create a distillate'.
Use when a task has multiple independent subtasks that can be executed concurrently by separate agents. Triggers when decomposed work has 2+ subtasks with no data dependencies, when subtasks operate on different files or codebase sections, when serial execution time would be significantly longer than parallel, or when independent analyses or deliverables need concurrent generation.
Evidence-first current-state research workflow for ECC. Use when the user wants fresh facts, comparisons, enrichment, or a recommendation built from current public evidence and any supplied local context.
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports.
Interactively onboard a project to agent-driven development by running a structured interview and generating a complete AGENTS.md (or CLAUDE.md). Use this skill whenever a user mentions "AGENTS.md", "CLAUDE.md", "agent behavior", "agent instructions", "agent config", "set up agent rules", "onboard agent", "configure claude code", "agent guardrails", "agent workflow", or asks how to tell an AI agent how to behave in their project — even if they just say "help me write AGENTS.md" or "what should go in CLAUDE.md". Always prefer this skill over ad-hoc agent instruction generation.
Tong Jincheng Perspective Skill - Analyze interpersonal relationships, romantic issues and human nature insights using the thinking framework of the 'Affectionate Grandmaster'
ModelScope integration. Manage data, records, and automate workflows. Use when the user wants to interact with ModelScope data.
Agent skill for agentic-payments - invoke with $agent-agentic-payments