浏览 front-depiction 维护的已发布 AI 技能，比较用途与说明，并通过来源仓库了解安装方式。
已收录技能
34收录技能的仓库 Stars 合计
376仓库 Forks
140平均每个技能的仓库 Stars
11同一仓库中的多个技能可能共享 Stars，合计包含重复仓库数据。
Master Effect pattern matching using Data.TaggedEnum, $match, $is, Match.typeTags, and Effect.match. Avoid manual _tag checks and Effect.either patterns. Use this skill when working with discriminated unions, A...
Write comprehensive tests using @effect/vitest for Effect code and vitest for pure functions. Use this skill when implementing tests for Effect-based applications, including services, layers, time-dependent eff...
Implement typeclasses with curried signatures and dual APIs for both data-first and data-last usage
Implement the VM pattern using Effect and Effect-Atom for reactive, testable frontend state management. Use this skill when building React applications with View Models that bridge domain services and UI.
Build composable React components using Effect Atom for state management. Use this skill when implementing React UIs that avoid boolean props, embrace component composition, and integrate with Effect's reactive...
Use @effect/platform abstractions for cross-platform file I/O, process spawning, HTTP clients, and terminal operations. Apply this skill when writing code that interacts with the filesystem, spawns processes, m...
Master Effect AI streaming response patterns including start/delta/end protocol, accumulation strategies, resource-safe consumption, and history management with SubscriptionRef.
Implement Effect services as fine-grained capabilities avoiding monolithic designs
Create and update ai-context.md files that document modules for AI assistants. Use when adding documentation for packages, apps, or external references that should be discoverable via /modules commands.
Conceptual guide to wide events (canonical log lines) for observability. Use when thinking about instrumentation strategy, span annotations, or designing what context to capture.
Implement typed error handling in Effect using Data.TaggedError, catchTag/catchTags, and recovery patterns. Use this skill when working with Effect error channels, handling expected failures, or designing error...
Build prompts for Effect AI using messages, parts, and composition operators. Covers the complete Prompt API for constructing, merging, and manipulating conversations with language models.
Design and compose Effect layers for clean dependency management
Parallel exploration of codebase questions by decomposing into independent tracks. Use when exploring architecture, understanding systems, or investigating complex questions that benefit from multiple perspecti...
Configure and compose AI provider layers using @effect/ai packages. Covers Anthropic, OpenAI, OpenRouter, Google, and Amazon Bedrock providers with config management, model abstraction, and runtime overrides fo...
Master Effect Schema composition patterns including Schema.compose vs Schema.pipe, transformations, filters, and validation. Use this skill when working with complex schema compositions, multi-step transformati...
Decide between Context Tag witness and capability patterns for dependency injection, understanding coupling trade-offs
Execute system commands and manage processes using Effect's Command module from @effect/platform. Use this skill when spawning child processes, running shell commands, capturing command output, or managing long...
Test Effect concurrency primitives including PubSub, Deferred, Latch, Fiber coordination, SubscriptionRef, and Stream. Use this skill when testing concurrent effects, event-driven systems, or fiber coordination...
Generate comprehensive predicates and orders for domain types using typeclass patterns
Implement reactive state management with Effect Atom for React applications
Orchestrate lawyer agents to review code for compliance with codebase laws. Spawns counsel in parallel to produce a unified legal brief.
Master the Effect AI LanguageModel service for text generation, structured output, streaming, and tool calling. Use when working with LLM interactions, schema-validated responses, or building conversational AI...
Create production-ready Effect domain models using Schema.TaggedStruct for ADTs, Schema.Data for automatic equality, with comprehensive predicates, orders, guards, and match functions. Use when modeling domain...
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。