A high-performance text embedding interface providing zero-markup access to top-tier models for vector search and RAG workflows.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install modesty-embedding-api
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install modesty-embedding-api using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Embedding API (SkillBoss)?
The Embedding API skill by SkillBoss is a powerful integration designed for developers who need reliable text embeddings for vector search without the overhead of managing multiple provider accounts. By leveraging Openclaw Skills, users gain access to over 648 APIs through a single, unified API key, ensuring a streamlined development process for AI-driven applications.
This skill is built on a philosophy of transparency and efficiency. It offers 0% markup pricing, meaning you pay exactly what the model provider charges. Whether you are building a recommendation engine, a semantic search tool, or a Retrieval-Augmented Generation (RAG) system, this skill provides a drop-in, OpenAI-compatible solution that eliminates vendor lock-in.
Embedding API (SkillBoss) Use Cases
- Generating text embeddings for vector databases and semantic search.
- Implementing RAG (Retrieval-Augmented Generation) in AI agents.
- Accessing premium embedding models like OpenAI text-embedding-3-large without individual provider billing.
- Reducing infrastructure costs by utilizing zero-markup AI API pricing.
- Prototyping multi-model systems that require frequent switching between embedding providers.
How Embedding API (SkillBoss) Works
- The user provides a text prompt or document that requires vectorization.
- The skill sends the input to the SkillBoss unified endpoint using the configured SKILLBOSS_API_KEY.
- SkillBoss routes the request to the specified model provider (defaulting to openai/text-embedding-3-large).
- The provider processes the text and returns a high-dimensional vector representation.
- The skill returns the raw embedding data to the calling agent or application for storage or similarity comparison.
Embedding API (SkillBoss) Setup
To get started with this skill, simply tell your agent:
set up skillboss.co/skill.md
Manual Configuration
If you prefer manual setup, follow these steps:
- Obtain your API key from the SkillBoss Console.
- Set your environment variable in your terminal or deployment environment:
export SKILLBOSS_API_KEY="your_api_key_here"
Embedding API (SkillBoss) Data Schema & Taxonomy
The skill utilizes an OpenAI-compatible request/response structure. Data is organized as follows:
| Field | Type | Description |
|---|---|---|
| model | string | The specific embedding model identifier (e.g., openai/text-embedding-3-large). |
| inputs | object | Contains the prompt key with the text to be embedded. |
| prompt | string | The actual string content intended for vectorization. |
| metadata | object | Includes usage statistics and provider-specific information. |
Embedding API (SkillBoss) Advanced Features
- Multi-model flexibility: Switch between 648+ APIs including chat, image, and video models using the same authentication.
- Zero markup pricing: Direct pass-through costs for all model provider tokens.
- OpenAI-compatible SDK support: Use any standard OpenAI library as a drop-in replacement.
- Extensive model library: Access to alternative high-quality models from Anthropic, Google, and DeepSeek via a single interface.
- High-scale performance: Optimized for production-grade vector search and high-throughput embedding generation.
SKILL.md
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