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Found 6,268 Skills
Explain English technical documents and text in Japanese with contextual understanding. Not a simple translator — reads the surrounding file or codebase context to provide deeper, more accurate explanations tailored for Japanese-speaking developers. Use when: "explain this English", "この英文を解説", "英語の解説", "en-explainer", "what does this mean", "この英文の意味", "英文を日本語で説明", "ドキュメントを解説", "README解説", "エラーメッセージの意味", "コメントの意味", "API仕様の解説", or when the user pastes English text and asks for explanation in Japanese. Also use when the user provides a file path and asks to explain specific English sections, or when they want to understand English code comments, error messages, config files, or technical documentation.
Creates production-grade, reusable skills that extend Claude's capabilities. This skill should be used when users want to create a new skill, improve an existing skill, or build domain-specific intelligence. Gathers context from codebase, conversation, and authentic sources before creating adaptable skills.
Effect-TS (Effect) guidance for TypeScript. Use when building, refactoring, reviewing, or explaining Effect code, especially for: typed error modeling (expected errors vs defects), Context/Layer/Effect.Service dependency wiring, Scope/resource lifecycles, runtime execution boundaries, schema-based decoding, concurrency/scheduling/streams, @effect/platform APIs, Effect AI workflows, and Promise/async migration.
Update PRD based on design decisions and strategic changes made during conversations
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
Apply graph-based thinking to visualize complex relationships and solve problems non-linearly. Use when mapping dependencies, analyzing systems, exploring interconnected concepts, or designing architectures.
Meta-skill that teaches the Agent how to discover, select, execute, chain, and observe skills in the skill system. Load this skill when you need to: (1) find which skill can handle a capability, (2) execute a skill operation via its entrypoint, (3) chain multiple skill operations together, (4) check policy before executing, or (5) log skill execution for observability. This skill makes YOU the router — you decide what to run, in what order, based on context.
Integrates Flowlines observability SDK into Python LLM applications. Use when adding Flowlines telemetry, instrumenting LLM providers, or setting up OpenTelemetry-based LLM monitoring.
Provides Complete patterns for testing async Python code with pytest: pytest-asyncio configuration, AsyncMock usage, async fixtures, testing FastAPI with AsyncClient, testing Kafka async producers/consumers, event loop and cleanup patterns. Use when: Testing async functions, async use cases, FastAPI endpoints, async database operations, Kafka async clients, or any async/await code patterns.
Handles sensitive data securely in Terraform. Use when managing passwords, API keys, database credentials, encryption keys, or other secrets. Covers Google Secret Manager integration, preventing secrets in state, IAM-based secret access, encryption, and security best practices.
Validate and optimize CLAUDE.md files using Anthropic's best practices for focused sessions. Detects contradictions, redundancy, excessive length (200+ lines), emphasis overuse (2%+ density), broken links, and orphaned sections. Scores health 0-50 points. Suggests safe automated fixes and extraction opportunities. Use when editing CLAUDE.md, before commits, when document grows past 200 lines, user says "optimize CLAUDE.md", "check contradictions", "validate documentation", or during quarterly reviews. Works with project and global CLAUDE.md files (.md extension). Based on Anthropic 2025 context engineering best practices.
Enforces the discipline of thinking about tests, features, and maintainability BEFORE writing implementation code. Use when starting new classes/methods, refactoring existing code, or when asked to "think about tests first", "design for testability", "what tests do I need", "test-first approach", or "TDD thinking". Promotes simple, maintainable designs by considering testability upfront. Works with any codebase requiring test coverage and quality standards.