GitHub
skill-builder
Create new Claude Code skills with proper SKILL.md format, frontmatter, and best practices. Use when building, scaffolding, or generating a new skill for Claude Code.
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content media llm ai AI 技能
发现 content media llm ai 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
分类目录: content media llm ai
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GitHub
llm-auto-update
LLM 모델 자동 업데이트 시스템 - 항상 최신 모델 정보 유지
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GitHub
aictxt-manager
生成、维护、修剪AICTXT文档，保持在CRAFT大小限制内。当AICTXT创建和更新时使用。
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GitHub
qdrant-rag-implementation
This skill provides guidance for implementing robust Qdrant vector database integration with RAG (Retrieval Augmented Generation) systems, including proper async client handling, error management, and performan...
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GitHub
learning-capture
Extract and consolidate key learnings, insights, and actionable takeaways from the current conversation session. Use when the user wants to capture, summarize, or document what was learned during the chat, crea...
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GitHub
devspeculate
Always use this skill to provide context on the codebase. Automatically initializes and references the Speculate documentation framework (coding rules, shortcuts, templates, and project specs) to ensure agents...
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GitHub
ensue-memory
Augmented cognition layer that makes users smarter by connecting conversations to their persistent knowledge tree. Use proactively when topics arise that might have prior knowledge, and when users ask to rememb...
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GitHub
telemetry-insights
Analyze AI coding session telemetry for usage patterns, token efficiency, and workflow optimization. Supports current session or historical time periods.
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GitHub
summarize-session
Compact the conversation context by summarizing what was accomplished and updating CLAUDE.md with any learnings. Use when context is getting long or when transitioning between work sessions.
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GitHub
azure-setup-guide
Research and generate Azure deployment guide with EasyAuth (Google + Facebook) and CosmosDB. This skill searches for current documentation and screenshots to produce an up-to-date setup guide at .docs/azure-set...
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GitHub
feature-planning
Focused task planning for ONE specific idea. Uses narrow→broad pattern - starts at user's focus point, expands context only as needed. Creates detailed task via task-board skill.
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GitHub
argentic-framework-development
Expert knowledge for building AI agents with Argentic - a Python microframework for async MQTT-based agents with multi-LLM support, custom tools, and multi-agent orchestration
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GitHub
atomic-blocks
Composable atomic blocks for categorical meta-prompting. Defines 16 reusable blocks across 4 layers (Assessment, Transformation, Refinement, Composition) that can be composed to build custom workflows. Enables...
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GitHub
meta-self
Master reference for categorical meta-prompting unified syntax. Contains all modifiers, operators, composition patterns, and execution protocols. Use this skill for self-reference when executing any prompt work...
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GitHub
llm4s-scala
LLM4S Scala functional LLM interfaces with Effect system integration. Use when building LLM applications in Scala with ZIO or Cats Effect, implementing type-safe AI pipelines with functional error handling, cre...
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GitHub
lmql-constraints
LMQL constraint-guided generation DSL for type-safe prompting with grammar constraints and logical conditions. Use when building structured LLM outputs with guaranteed format compliance, implementing constraine...
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GitHub
categorical-meta-prompting
Full categorical framework for meta-prompting with verified laws. Use when implementing functor-based task routing, monadic iterative refinement, comonadic context extraction, or quality-tracked composition. In...
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GitHub
recursive-meta-prompting
Recursive Meta-Prompting (RMP) implementation with unified categorical syntax. Supports @mode:iterative, @quality: thresholds, >=> Kleisli composition, and comonadic context extraction. Use when implementing it...
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GitHub
dynamic-prompt-registry
Dynamic prompt registry with unified categorical syntax. Supports @skills:discover(), @skills:compose(A⊗B), Reader monad for runtime lookup, and quality-tracked prompt libraries. Use for meta-prompts referencin...
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GitHub
prompt-dsl
Domain-specific language for categorical prompt composition with functor combinators and natural transformation operators. Use when building composable prompt templates, implementing typed prompt algebras, crea...
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GitHub
dspy-categorical
DSPy compositional prompt optimization with categorical signatures, module chaining, and automated prompt tuning. Use when building declarative LLM programs with typed signatures, composing multi-step reasoning...
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GitHub
effect-ts-ai
@effect/ai integration patterns for categorical AI composition, typed error handling, and production prompt pipelines. Use when building AI applications with Effect-TS, composing LLM calls with typed errors, cr...
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GitHub
cc2-research-framework
CC2.0 seven-function research workflow (observe, reason, create, orchestrate, learn, verify, deploy) for categorical AI research. Use when conducting systematic research on categorical AI topics, coordinating m...
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GitHub
guidance-grammars
Guidance library grammar-constrained generation with categorical structure. Use when implementing structured LLM outputs with grammar constraints, building template-based generation with guaranteed formats, cre...
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。