Total 50,611 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Analyze development sessions, capture learnings, and improve Claude Code instructions. Use when the user wants to reflect on a session, improve CLAUDE.md, extract learnings, or optimize AI-human collaboration. Supports two modes: quick (default) focuses on CLAUDE.md improvements, deep mode performs comprehensive session analysis with learning capture.
Neta API space and world‑view browsing skill — browse worldbuilding, sub‑spaces, and playable content by space/hashtag. Use this skill when the user talks about worlds/spaces/universes/scenes, or wants to browse characters and gameplay based on space and activity structure. Do not use it for concrete media creation (handled by neta-creative).
Neta API community skill — browse interactive feeds, view collection details, like and interact with content, and browse content by tags and characters in a community context. Use this skill when the user wants to “see what people are making”, “scroll the feed”, or “interact with works”. Do not use it for taxonomy/keyword‑level research (handled by neta-suggest) or for generating images/videos/songs (handled by neta-creative).
Operate the external task-management CLI (tk) as source of truth for agent execution tracking. Invoke when any SPEC comes up for implementation, when the user asks to track tasks, check what to work on next, see task status, manage work dependencies, or close/abandon tasks. For coordination-tier artifacts (EPIC, VISION, JOURNEY), swain-design must decompose into child SPECs first — this skill tracks the children, not the container.
Multi-agent management workflow — task delegation, progress monitoring, quality verification with regression testing, feedback delivery, and cross-review orchestration. Use this skill when coordinating multiple agents on a shared task, monitoring delegated work, ensuring quality across agent outputs, or implementing a multi-phase plan (3+ phases or 10+ file changes).
Use this skill when building production LLM applications, implementing guardrails, evaluating model outputs, or deciding between prompting and fine-tuning. Triggers on LLM app architecture, AI guardrails, output evaluation, model selection, embedding pipelines, vector databases, fine-tuning, function calling, tool use, and any task requiring production AI application design.
P7 Senior Engineer mode — solution-driven execution under P8 supervision. Use when user says 'P7模式', '方案驱动', or when spawned as sub-task executor by P8. Produces: implementation plan + code + 3-question self-review, delivered via [P7-COMPLETION].
Let's Enhance integration. Manage data, records, and automate workflows. Use when the user wants to interact with Let's Enhance data.
This skill should be used when the user needs to customize a resume for a specific job posting while maintaining truthfulness. Use when adapting an existing resume to match a job description, repositioning experience for a new role, or aligning resume language with target role keywords and requirements.
Build, run, and visualize multi-step AI generation workflows. The AI architect translates natural language descriptions into connected node graphs — chain image generation, video creation, enhancement, and editing into automated pipelines.
Convert photos (people, pets, objects, logos) into 4 animated GIF stickers with captions. Use when: user wants to create cartoon stickers, GIF expressions, emoji packs, animated avatars, or convert photos to Funko Pop / Pop Mart blind box style animations. Triggers: sticker, GIF, cartoon, emoji, expression pack, avatar animation.
Interact with the learning system: show stats, list/search accumulated knowledge, and graduate mature entries into agents/skills. Backed by learning.db (SQLite + FTS5). Use when user says "retro", "retro list", "retro search", "retro graduate", "check knowledge", "what have we learned", "knowledge health", "graduate knowledge".