Activates the Pickle Rick persona. Use this ONLY when the user explicitly requests to start the "Pickle Rick" mode or loop. DO NOT use this for general greetings (e.g., "hi") normal assistance.
原文の言語: 英語
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このリポジトリの skills
SkillsMP は majiayu000/claude-skill-registry から 5,417 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
majiayu000/claude-skill-registry収集済み skill 5,417 件中 40 件を表示しています。
Activates the Pickle Rick persona. Use this ONLY when the user explicitly requests to start the "Pickle Rick" mode or loop. DO NOT use this for general greetings (e.g., "hi") normal assistance.
原文の言語: 英語
Detect user's intent from their message and activate the right workflow silently.
原文の言語: 英語
Structured checkpoint format for requesting human input. When an agent needs a decision, it must stop, present context, show options, and wait. Activate when delegating to subagents, running background tasks, or hitting any decision point that requires human…
原文の言語: 英語
MANDATORY protocol enforcing knowledge check before EVERY response - prevents explaining systems without reading docs, claiming without verification, and ignoring auto-loaded context
原文の言語: 英語
Validation agent that validates plan tech choices against current best practices
原文の言語: 英語
Interactive onboarding agent for content marketing associate candidates and vault orientation for Charlie. Walks candidates through the OpenEd content system, discovers their strengths, guides them to produce real output, and helps them write a contract…
原文の言語: 英語
Ultimate autonomous execution engine. Plan → Execute → Test → Never Stop Until Done. Use when the user wants hands-off completion with no questions, automatic recovery from any failure, and proven results.
原文の言語: 英語
Short alias for vc-phase-loop. Use when the user invokes "vcf:" or "use vcf:" and wants maximum hands-off completion.
原文の言語: 英語
Create and configure VoltAgent AI agents with tools, memory, hooks, and sub-agents. Use when building AI agents, adding agent tools, configuring VoltAgent memory, creating multi-agent workflows, or debugging VoltAgent integrations.
原文の言語: 英語
Focused task execution for persistent team workers. Use when implementing features, following scope constraints, using TDD red-green-refactor, validating with browser/API/unit tests, or participating in voting consensus. Triggers on worker execution, feature…
原文の言語: 英語
Execute beads autonomously within a track. Handles bead-to-bead context persistence via Agent Mail, uses preferred tools from AGENTS.md, and reports progress to orchestrator.
原文の言語: 英語
Train and deploy generative UI agents using behavioral programming constraints, A2A protocol for agent interoperability, and pattern registry for composition. Use when working with agent training, trajectory generation, reward computation, A2A integration, or…
原文の言語: 英語
Complete fixer agent workflow including report discovery, validation strategy (HIGH/MEDIUM/FALSE_POSITIVE confidence), fix application, and fix report generation. Use when implementing or updating fixer agents.
原文の言語: 英語
Step-by-step validation workflow for checker agents - initialize report, discover content, validate progressively, finalize with summary. Use when implementing or updating checker agents.
原文の言語: 英語
Use when the user wants to create a new Claude Code subagent. Guides subagent creation with focused prompts and constrained tool access.
原文の言語: 英語
Create a reusable skill for evaluating fine-tuned models, benchmarking performance, and detecting quality regressions
原文の言語: 英語
Create your llmops-fine-tuner skill from Unsloth documentation before learning fine-tuning theory
原文の言語: 英語
"This skill should be used when evaluating whether fine-tuning is appropriate for an LLMOps project. Use when analyzing domain use cases, comparing training methods, calculating ROI, or deciding between API-based and self-hosted solutions."
原文の言語: 英語
"This skill should be used when fine-tuning for personality, brand voice, or communication style. Use when the goal is HOW a model communicates rather than WHAT it knows."
原文の言語: 英語
"This skill should be used when fine-tuning language models for reliable tool-calling and structured output generation. Use when creating agent backends, training for function calling, or building models that need 95%+ JSON accuracy."
原文の言語: 英語
"This skill should be used when combining multiple LoRA adapters or fine-tuned models into a single unified model. Use when students have trained separate adapters for different capabilities (persona, tool-calling, domain knowledge) and need to merge them…
原文の言語: 英語
Create your model-alignment skill from TRL documentation before learning DPO theory
原文の言語: 英語
Create your model-serving skill from Ollama documentation before learning deployment theory
原文の言語: 英語
Consolidate all Part 8 skills into a production-ready llmops-fine-tuner skill
原文の言語: 英語
ADHD-optimized code explainer. Generates layered, scannable explanations with hooks, maps, and progress markers.
原文の言語: 英語
Build RAG (Retrieval-Augmented Generation) agents with Google ADK and Vertex AI RAG Engine. Use when implementing document Q&A, knowledge base search, or citation-backed responses. Covers VertexAiRagRetrieval tool, corpus setup, and citation formatting.
原文の言語: 英語
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
原文の言語: 英語
Context-efficient tool management via search, deferred loading, and programmatic calling
原文の言語: 英語
Iteratively refine a product spec by debating with multiple LLMs (GPT, Gemini, Grok, etc.) until all models agree. Use when user wants to write or refine a specification document using adversarial development.
原文の言語: 英語
Expert AI engineer specializing in AI system design, model implementation, and production deployment. Masters multiple AI frameworks and tools with focus on building scalable, efficient, and ethical AI solutions from research to production.
原文の言語: 英語
Imported skill agents from vercel
原文の言語: 英語
Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs,…
原文の言語: 英語
Design and implement evaluation frameworks for AI agents. Use when testing agent reasoning quality, building graders, doing error analysis, or establishing regression protection. Framework-agnostic concepts that apply to any SDK.
原文の言語: 英語
Expert LLM architect specializing in large language model architecture, deployment, and optimization. Masters LLM system design, fine-tuning strategies, and production serving with focus on building scalable, efficient, and safe LLM applications.
原文の言語: 英語
Layer 4: Learning and Pattern Extraction for Cognitive Surrogate Systems
原文の言語: 英語
Central authority for Claude Agent SDK (TypeScript and Python SDKs). Covers SDK installation, authentication (Anthropic key, Bedrock, Vertex), sessions and resumption, forking sessions, streaming vs single mode, custom tools, permissions (allowedTools,…
原文の言語: 英語
Guidance for selecting appropriate AI model (sonnet vs haiku) based on task complexity, reasoning requirements, and performance needs. Use when implementing agents or justifying model selection.
原文の言語: 英語
Guidance for selecting appropriate AI model (sonnet vs haiku) based on task complexity, reasoning requirements, and performance needs. Use when implementing agents or justifying model selection.
原文の言語: 英語
Run 150+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating…
原文の言語: 英語
LLM prompt management and evaluation platform. Version prompts, run A/B tests, evaluate with metrics, and deploy with confidence using Agenta's self-hosted solution.
原文の言語: 英語