asr
Implement speech-to-text (ASR/automatic speech recognition) capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to transcribe audio files, convert speech to text, build voice input featu...
发现 documentation 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。
Implement speech-to-text (ASR/automatic speech recognition) capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to transcribe audio files, convert speech to text, build voice input featu...
Implement AI image generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to create images from text descriptions, generate visual content, create artwork, design assets, or buil...
Implement text-to-speech (TTS) capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to convert text into natural-sounding speech, create audio content, build voice-enabled applications, o...
Implement large language model (LLM) chat completions using the z-ai-web-dev-sdk. Use this skill when the user needs to build conversational AI applications, chatbots, AI assistants, or any text generation feat...
Implement vision-based AI chat capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to analyze images, describe visual content, or create applications that combine image understanding wit...
Implement web search capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to search the web, retrieve current information, find relevant content, or build applications with real-time web...
Critically assesses generated review comments for usefulness, accuracy, and appropriateness, adding assessment sections.
Detects hallucinations, timeline fabrications, and unverified assumptions in agent output. Use when reviewing sub-agent results, receiving research findings, validating claims that seem suspicious, or when outp...
Quick delegation template for sub-agent prompts. Use when assigning work to a sub-agent, before invoking the Task tool, or when preparing prompts for specialized agents. Provides the WHERE-WHAT-WHY framework. F...
Forces hypothesis-driven scientific reasoning for complex problems. Use when debugging strange behavior, investigating root causes, designing architecture, performing complex refactoring, or when initial attemp...
Annotates agent prompts with structural XML tags for comprehension, gap detection, and skill extraction. Use when analyzing agent prompt structure, comparing agents across projects, or identifying reusable vs w...
Opinionated constraints for building better interfaces with agents.
Refine plans through multi-agent expert discussion. Use when user says "get multiple expert opinions on this plan", "I want different perspectives on this approach", "have the agents discuss this strategy", "re...
Build a unified, ADHD-friendly web UI that consolidates 70+ CLI tools into a beautiful liquid glass interface for the AI File Organizer. Use when creating the complete frontend application that replaces all ter...
Orchestrates multi-agent workflows by delegating ALL tasks to spawned subagents via /spawn command. Parallelizes independent work, supervises execution, tracks progress in UUID-based output directories, and gen...
Expert assistant for creating Claude Code custom slash commands. Guides command file structure, YAML frontmatter configuration, variable syntax, and best practices. Triggers on keywords: writing commands, creat...
Expert assistant for authoring Claude Code skills. Creates precise SKILL.md files with proper YAML frontmatter, validates naming conventions, and applies official best practices. Triggers on keywords: writing s...
Guide to spences10's Claude Code ecosystem. Use when user asks which tool to use, how tools relate, or needs help choosing between MCP servers, skills, or CLIs.
Guide for creating, testing, and deploying effective skills. Use when users want to create a new skill, update an existing skill, verify skills work before deployment, or extend Claude's capabilities with speci...
Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database connections, API clients, user context, or any external resources.
Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configurat...
Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.
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。