token-formatter
Convert verbose docs/markdown/text into token-efficient formats. Use when user wants to reduce token count, compress content for LLM context, or optimize for AI consumption.
Convert verbose docs/markdown/text into token-efficient formats. Use when user wants to reduce token count, compress content for LLM context, or optimize for AI consumption.
Generate extractive summaries from long text documents. Control summary length, extract key sentences, and process multiple documents.
Transcribe audio files using OpenAI's gpt-4o-mini-transcribe model with vocabulary hints and text replacements. Requires uv (https://docs.astral.sh/uv/).
Extract named entities (people, organizations, locations, dates) from text using NLP. Use for document analysis, information extraction, or data enrichment.
Analyze customer interview transcripts (SRT or plain text) to generate thematic breakdowns with summary, quotes, topics, timestamps, and full transcript. Use when given video transcripts or asked to create chapter markers.
Detect language of text with confidence scores, support for 50+ languages, and batch text classification.
Transcribe audio/video with AssemblyAI (local upload or URL), plus subtitles + paragraph/sentence exports.
Transcribe audio files via OpenRouter using audio-capable models (Gemini, GPT-4o-audio, etc).
Audio transcription using local whisper.cpp server with CUDA acceleration. HTTP API for speech-to-text conversion.
Provides context-aware compaction guidance with intelligent checkpointing. Monitors context during long tasks and suggests checkpoints before compaction interrupts your work.
Provides a Model Context Protocol (MCP) server interface to the skills library, allowing any MCP-compliant agent (e.g. Claude Desktop) to invoke Antigravity skills as native tools.
Use when planning, scaffolding, validating, or packaging Claude skills inside Advanced Memory MCP.
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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Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. Keywords: ๅๅปบๆ่ฝ, ๆ่ฝๅผๅ, ๆๅปบclaudeๆ่ฝ, ๆ่ฝ่ฎพ่ฎก, ๆ่ฝๆจกๆฟ, create skill, build skill, develop skill, skill creation, skill development, skill template, skill design, skill builder, skill generator, ๆ่ฝ็ๆๅจ, ๆ่ฝๆๅปบๅจ
Comprehensive template and guidelines for documenting Field Agents including technical specifications, system prompts, tool specifications, user interactions, and standardized documentation structure
One-way TTS mode - Claude speaks aloud while user types. Use when user says: 'speak', 'read aloud', 'vocal on', 'lis-moi', 'parle-moi', or wants Claude to vocalize responses without responding vocally themselves. For bidirectional voice conversation (user speaks too), use /conversation instead.
Official skill generator for VS Code Agent Skills; scaffolds new skills with correct directory structure and validation, and is the upstream dependency for authoring or modifying any other skill in this repository.
Apply prompting techniques when creating prompts, agents, commands, system instructions, or SKILL.md files. Use for XML tags, multishot examples, chain-of-thought, response prefilling, and Claude 4-specific patterns.
Prioritize brevity, directness, and clarity in all responses with minimal token usage.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Comprehensive guide for debugging Claude Agent SDK errors, TypedDict contracts, and internal SDK processing issues
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