发现优质的 AI Agent 技能

This skill configures OpenClaw memory search to use Ollama as the **embeddings server** via its OpenAI-compatible `/v1/embeddings` endpoint.

"Track, analyze, and optimize AI API token costs across 10 providers (Anthropic, OpenAI, Google, Mistral, xAI, Kimi, Qwen, DeepSeek, Meta, MiniMax) — 44 models. Set budgets, get alerts, compare costs, and get optimization suggestions. Zero dependencies, local-only, MIT licensed."

> **For Claude Code** | 适用于 Claude Code > > **Note**: This methodology works with any multi-agent system (Cursor, LangChain, OpenAI Assistants, OpenClaw, etc.). This file is the Claude Code skill wrapper. See [README.md](README.md) for platform-agnostic usage. > > **说明**：本方法论适用于任何多智能体系统（Cursor、LangChain、OpenAI Assistants、OpenClaw 等）。本文件是 Claude Code 技能封装。通用用法见 [README.md](README.md)。

| Model | Range | Examples | |-------|--------|----------| | Subscription | $9-99/mo | Zapier $20-799 | | Pay-per-task | $0.01-1 | Apify | | Usage | $0.001/token | OpenAI |

Use this skill for **multiple OpenAI OAuth login accounts managed inside OpenClaw**, especially OpenClaw's own `openai-codex` OAuth accounts, not just plain Codex CLI account files.

**Version:** 2.0.0 (Production-Grade Enhancement) **Status:** Enhanced with AI safety research and meta-learning **Research Base:** MIRI, DeepMind, OpenAI, Stanford, MIT

--- This skill is designed for use on the Tasking.tech agent platform (https://tasking.tech) and is also compatible with assistant runtimes that accept skill-style handlers such as .claude, .openai, and .mistral. Use this skill for both Claude code and Tasking.tech agent source.

--- This skill is designed for use on the Tasking.tech agent platform (https://tasking.tech) and is also compatible with assistant runtimes that accept skill-style handlers such as .claude, .openai, and .mistral. Use this skill for both Claude code and Tasking.tech agent source.

Local speech-to-text using faster-whisper — a CTranslate2 reimplementation of OpenAI's Whisper that runs **4-6x faster** with identical accuracy. With GPU acceleration, expect **~20x realtime** transcription (a 10-minute audio file in ~30 seconds).

**Skill**: `podcast-generation` **Purpose**: Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model **Focus**: Script generation, text-to-speech, audio processing, WebSocket streaming

Generate real audio narratives from text content using Azure OpenAI's Realtime API.

This skill guides users through configuring OpenRouter as their LLM provider on this AgentBox instance. OpenRouter gives access to models from Anthropic, OpenAI, Google, Meta, and others through a single API key.