القائمة
Skills في هذا المستودع
جمع SkillsMP عدد ٥٬٤١٧ من skills من majiayu000/claude-skill-registry. افتح أي skill لمراجعة مصدره وتفاصيله.
majiayu000/claude-skill-registryعرض ٤٠ من أصل ٥٬٤١٧ skills مجمعة.
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.
لغة النص الأصلي: الإنجليزية
Detect user's intent from their message and activate the right workflow silently.
لغة النص الأصلي: الإنجليزية
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…
لغة النص الأصلي: الإنجليزية
MANDATORY protocol enforcing knowledge check before EVERY response - prevents explaining systems without reading docs, claiming without verification, and ignoring auto-loaded context
لغة النص الأصلي: الإنجليزية
Validation agent that validates plan tech choices against current best practices
لغة النص الأصلي: الإنجليزية
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…
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
Short alias for vc-phase-loop. Use when the user invokes "vcf:" or "use vcf:" and wants maximum hands-off completion.
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
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…
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
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…
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
Step-by-step validation workflow for checker agents - initialize report, discover content, validate progressively, finalize with summary. Use when implementing or updating checker agents.
لغة النص الأصلي: الإنجليزية
Use when the user wants to create a new Claude Code subagent. Guides subagent creation with focused prompts and constrained tool access.
لغة النص الأصلي: الإنجليزية
Create a reusable skill for evaluating fine-tuned models, benchmarking performance, and detecting quality regressions
لغة النص الأصلي: الإنجليزية
Create your llmops-fine-tuner skill from Unsloth documentation before learning fine-tuning theory
لغة النص الأصلي: الإنجليزية
"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."
لغة النص الأصلي: الإنجليزية
"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."
لغة النص الأصلي: الإنجليزية
"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."
لغة النص الأصلي: الإنجليزية
"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…
لغة النص الأصلي: الإنجليزية
Create your model-alignment skill from TRL documentation before learning DPO theory
لغة النص الأصلي: الإنجليزية
Create your model-serving skill from Ollama documentation before learning deployment theory
لغة النص الأصلي: الإنجليزية
Consolidate all Part 8 skills into a production-ready llmops-fine-tuner skill
لغة النص الأصلي: الإنجليزية
ADHD-optimized code explainer. Generates layered, scannable explanations with hooks, maps, and progress markers.
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
لغة النص الأصلي: الإنجليزية
Context-efficient tool management via search, deferred loading, and programmatic calling
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
Imported skill agents from vercel
لغة النص الأصلي: الإنجليزية
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,…
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
Layer 4: Learning and Pattern Extraction for Cognitive Surrogate Systems
لغة النص الأصلي: الإنجليزية
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,…
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية
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…
لغة النص الأصلي: الإنجليزية
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.
لغة النص الأصلي: الإنجليزية