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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devops llm ai AI 技能
发现 devops 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。
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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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GitHub
langgraph-orchestration
LangGraph stateful multi-agent graphs with categorical coordination patterns and cyclic workflows. Use when building stateful AI agent systems, implementing multi-agent orchestration with conditional routing, c...
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GitHub
arxiv-categorical-ai
Systematic analysis patterns for categorical AI papers (Gavranović, de Wynter, Bradley, Zhang). Use when analyzing academic papers on categorical deep learning, extracting categorical structures from AI researc...
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GitHub
discopy-nlp
DisCoPy categorical quantum NLP for string diagrams, monoidal categories, and compositional semantics in Python. Use when implementing compositional distributional semantics, building string diagram computation...
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GitHub
voltagent-multiagent
VoltAgent multi-agent system design with natural transformation coordination between agents. Use when building TypeScript multi-agent AI systems, implementing agent coordination with categorical patterns, desig...
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GitHub
prompt-benchmark
Systematic prompt evaluation framework with MATH, GSM8K, and Game of 24 benchmarks. Use when evaluating prompt effectiveness on standard benchmarks, comparing meta-prompting strategies quantitatively, measuring...
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GitHub
quality-enriched-prompting
[0,1]-enriched category implementation for gradient-based prompt quality optimization. Use when implementing quality-aware prompt systems, building enriched categorical structures for prompt evaluation, creatin...
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GitHub
design-system-context
Managing design tokens and system context for LLM-driven UI development. Covers loading, persisting, and optimizing design decisions within context windows.
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GitHub
skill-learning
Extract actionable knowledge from external sources and enhance existing skills using 4-tier novelty framework. Use when learning from URLs, documentation, or codebases. Use for enhancing existing skills or crea...
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GitHub
claude-guide
Navigate Claude Code documentation and get quick answers about configuration, MCP, plugins, and best practices.
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GitHub
effect-foundations
Core Effect foundations and style for a coding agent. Use when starting an Effect task, choosing operators, or structuring a small pipeline.
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GitHub
fuzzy-selecting
Provides interactive fuzzy finder for selecting items from any list with preview capabilities. Use this skill when choosing from search results, files, processes, or any command output
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GitHub
tech-specification
The master skill for generating technical specifications. Identifies project technology and delegates deep analysis to specialized sub-skills.
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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。