358 skills · sorted by relevance
Build command-line interfaces for graphical applications in Cursor using the CLI-Anything workflow. It supports creating and extending these interfaces, running tests, checking required criteria, and listing tools through slash commands or natural-language requests.
Evaluates task complexity and selects a small set of existing skills for work spanning multiple areas. Uses agent-memory-mcp to record and retrieve successful combinations, while keeping simple tasks within the agent’s ordinary capabilities.
Create, improve, or evaluate an existing skill from workflows, prompts, SOPs, scripts. Use for migration/release/package, routing, evals/tests, install/trust checks, 优化已有 skill, 补 trigger 评测. Exclude summary/translation/docs, brainstorming, one-off prompts, copy-only edits, outline-only requests.
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A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
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antigravity-skill-orchestrator workflow skill. Use this skill when the user needs A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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antigravity-skill-orchestrator workflow skill. Use this skill when the user needs A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Agent Orchestrator workflow skill. Use this skill when the user needs Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Agent Orchestrator workflow skill. Use this skill when the user needs Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
The English summary is being prepared. Showing the original description.
A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
The English summary is being prepared. Showing the original description.
A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
The English summary is being prepared. Showing the original description.
Meta-skill: Structured thinking as a 3-phase workflow. Combines analysis (think), ideation (brainstorm), and decision-making (decide) into one continuous process.
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A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
The English summary is being prepared. Showing the original description.
Meta-skill para criar, editar, avaliar e otimizar skills do kit. Use quando adicionar nova skill, refatorar skill existente, ou medir qualidade de descoberta de skill (description triggering). Trigger em: "criar nova skill", "nova capacidade", "skill author", "skill creator", "editar skill", "avaliar skill", "skill eval", "otimizar description", "meta-skill", "kit governance".
The English summary is being prepared. Showing the original description.
A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
The English summary is being prepared. Showing the original description.
A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
The English summary is being prepared. Showing the original description.
A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.
The English summary is being prepared. Showing the original description.
Choose the right engineering skills for a task and decide their order, from clarifying requirements to deployment. This guide also defines shared practices for stating assumptions, resolving uncertainty, keeping scope focused, and verifying completed work.
Find and install command-line tools that let AI agents operate professional software. Search by task or category, check which workflow capabilities are available locally, and install the specific tools needed for a multi-tool project.
Inventory local skills within a requested scope, rank candidates against a task, and prepare a coordination plan showing their order and data flow. Project assignments help prioritize relevant skills without automatically launching agents or executing skills.
Check Agent Skills for documentation structure and Python script behavior, then score quality and security posture. Get grades and improvement priorities, and use pass criteria in pre-commit checks or continuous integration, which runs checks automatically.
Turn documentation, code, and specifications into reusable Agent Skills. Define when each skill should activate, organize supporting references, add reproducible examples, and check new or existing skills with templates, a checklist, and a validator.
Analyze an existing codebase to identify reusable design patterns in components, services, APIs, styling, and refresh scheduling. Produces structured descriptions with representative code, conventions, dependencies, and adaptation notes for reuse or later conversion into skills.
Darwin Skill 2.0 (达尔文.skill 2.0): autonomous skill optimizer, v2.0 integrates Microsoft Research SkillLens (arXiv 2605.23899) 9-dim rubric + SkillOpt (arXiv 2605.23904) validation-gated design + human-in-the-loop checkpoints. Evaluates SKILL.md files using a 9-dimension rubric (structure + effectiveness + meta-skill blacklists), runs hill-climbing with git version control, spawns independent judge agents for blind evaluation, validates improvements through test prompts with auto-break on diminishing returns, and generates visual result cards. Use when user mentions "优化skill", "skill评分", "自动优化", "auto optimize", "skill质量检查", "达尔文", "darwin", "帮我改改skill", "skill怎么样", "提升skill质量", "skill review", "skill打分".
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Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
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