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Found 3,471 Skills
Cross-platform landscape scan before planning or implementation. Researches context, workarounds, existing solutions, and structural gaps, then writes reusable survey artifacts for OMC, OMX, OHMG, and general agent workflows.
This skill should be used when the user asks to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
Standalone squad manager — creates, inspects, validates, and manages squads (multi-agent teams). Scaffolds directories, agents, tasks, workflows. Registers squads for slash commands. Works independently without AIOS. Activates on: create squad, list squads, add agent, validate squad, run workflow, inspect squad, manage squad.
Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
AI-агент для управления Facebook рекламой. Вызывай для анализа, оптимизации, создания кампаний и отчётов.
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Generate objective reference check reports about the user from real AI collaboration data — session history, git logs, GitHub profile, and memory files. Like a colleague writing a professional reference, but grounded in actual shared work. Use whenever the user asks to evaluate them as a developer, wants a reference letter, work style analysis, introduced by my agents content, interview prep from collaboration history, or blog topics from past discussions. Triggers on: write a reference, analyze my work patterns, what do you think of me, 나에 대한 레퍼런스 써줘, 내 작업 스타일 분석해줘. Not for general code review, architecture docs, cover letters, or codebase-only analysis.
Modern Python 3.12+ patterns your AI agent should use. Type hints, async/await, Pydantic v2, uv, match statements, and project structure.
Generate a personalized portfolio site from agent-reference reports and deploy it to GitHub Pages. The site reflects the user's working style as observed by their AI collaborators — AI analyzes the reports, proposes a design concept, scaffolds an Astro site with concept-based theming, and deploys to {username}.github.io. Use this skill whenever the user asks to "build my portfolio", "create portfolio site", "make a site from my reports", "deploy to github pages", "github.io site", or says things like "포트폴리오 사이트 만들어줘", "사이트 배포해줘", or wants to turn agent-reference reports into a live website. Also triggers when the user has agent-reference reports ready and wants to publish them as a site, wants a personal site generated from AI collaboration data, or asks to update/redeploy an existing agent portfolio. Do NOT use for general Astro development, generic website building, agent-reference analysis without site generation, or resume writing that does not involve deploying a site.
Generates high-quality Gherkin (BDD) scenarios from functional requirements using a two-agent iterative cycle: a generator agent that creates/modifies the Gherkin and a reviewer agent that validates it and proposes improvements. The cycle repeats automatically until the Gherkin passes review. Use this skill whenever the user mentions: "generate Gherkin", "BDD scenarios", "Gherkin test cases", "Feature/Scenario/Given/When/Then", "requirements to Gherkin", "BDD specifications", or asks to transform functional requirements into behaviour tests. Also applies when the user brings a requirements document and wants test cases, acceptance criteria, or user stories with executable examples.
Audit skill SKILL.md files for compliance with the agentskills.io specification. Checks frontmatter fields (name, description, compatibility, metadata, argument-hint) and metadata sub-fields (author, scope, confirms). Use when adding new skills, reviewing skill quality, or ensuring all skills follow the spec. Triggers: "audit skills", "check skill spec", "skill compliance", "are my skills up to spec", "/claude-skill-spec-audit".
Expert guidance for LangChain and LangGraph development with Python, covering chain composition, agents, memory, and RAG implementations.