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All Skills

Total 30,768 skills, AI & Machine Learning has 4969 skills

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Showing 12 of 4969 skills

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AI & Machine Learninggoogle/adk-docs

adk-eval-guide

MUST READ before running any ADK evaluation. ADK evaluation methodology — eval metrics, evalset schema, LLM-as-judge, tool trajectory scoring, and common failure causes. Use when evaluating agent quality, running adk eval, or debugging eval results. Do NOT use for API code patterns (use adk-cheatsheet), deployment (use adk-deploy-guide), or project scaffolding (use adk-scaffold).

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3
AI & Machine Learninggoogle/adk-docs

adk-observability-guide

MUST READ before setting up observability for ADK agents or when analyzing production traffic, debugging agent behavior, or improving agent performance. ADK observability guide — Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations, and troubleshooting. Use when configuring monitoring, tracing, or logging for agents, or when understanding how a deployed agent handles real traffic.

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3
AI & Machine Learninggoogle/adk-docs

adk-cheatsheet

MUST READ before writing or modifying ADK agent code. ADK API quick reference for Python — agent types, tool definitions, orchestration patterns, callbacks, and state management. Includes an index of all ADK documentation pages. Do NOT use for creating new projects (use adk-scaffold).

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3
AI & Machine Learninggoogle/adk-docs

adk-scaffold

MUST READ before creating or enhancing any ADK agent project. Use when the user wants to build a new agent (e.g. "build me a search agent") or enhance an existing project (e.g. "add CI/CD to my project", "add RAG").

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3
AI & Machine Learningmcollina/skills

init

Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project-specific rules that agents cannot infer from reading the codebase. Use when setting up agent instructions or Claude configuration for a new repository, when an existing AGENTS.md is too long, generic, or stale, when agents repeatedly make avoidable mistakes, or when repository workflows have changed and the agent configuration needs pruning. Applies a discoverability filter—omitting anything Claude can learn from README, code, config, or directory structure—and a quality gate to verify each line remains accurate and operationally significant.

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3
AI & Machine Learningoil-oil/bulkgen-skill

bulkgen

Bulk AI image generation via the BulkGen API. Use whenever users ask to generate one or many AI images — even simple requests like "generate an image", "edit this image", "make variations", or "create AI art" should trigger this skill. Handles single images, grids, batches, variations, reference-image editing, expiring result downloads, and HTML preview handoff pages. Works for English and Chinese requests like "生成图片", "批量生成", "图生图", "做一个 3x3 宫格", or "给我做九宫格变体".

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3 scripts/Attention
AI & Machine Learningclaude-office-skills/skil...

deep-research

Conduct comprehensive research on any topic. Synthesize information from multiple angles, provide structured analysis, and generate detailed research reports.

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3
AI & Machine Learningnowledge-co/community

save-handoff

Save a concise handoff summary only when the user explicitly requests it. Use this for resumable progress notes in generic agent environments where a real session importer is not guaranteed.

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3
AI & Machine Learningpetekp/agent-skills

autonomous-agent-readiness

Assess a codebase's readiness for autonomous agent development and provide tailored recommendations. Use when asked to evaluate how well a project supports unattended agent execution, assess development practices for agent autonomy, audit infrastructure for agent reliability, or improve a codebase for autonomous agent workflows. Triggers on requests like "assess this project for agent readiness", "how autonomous-ready is this codebase", "evaluate agent infrastructure", or "improve development practices for agents".

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3
1 scripts/Checked
AI & Machine Learningcatlog22/claude-code-work...

parallel-dev-cycle

Multi-agent parallel development cycle with requirement analysis, exploration planning, code development, and validation. Orchestration runs inline in main flow (no separate orchestrator agent). Supports continuous iteration with markdown progress documentation. Triggers on "parallel-dev-cycle".

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3
AI & Machine Learningcatlog22/claude-code-work...

workflow-execute

Autonomous workflow execution pipeline with CSV wave engine. Session discovery → plan validation → IMPL-*.json → CSV conversion → wave execution via spawn_agents_on_csv → results sync. Task JSONs remain the rich data source; CSV is brief + execution state.

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3
AI & Machine Learningpluginagentmarketplace/cu...

agent-memory

Implement agent memory - short-term, long-term, semantic storage, and retrieval

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3
2 scripts/Checked
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