# semantic-search-project

> semantic-search-project — phaja-semantic-search-project. Use this tool when you need to efficiently retrieve context-based text using semantic search, solving problems of slow or irrelevant search results. It takes in text queries as input and outputs relevant results, leveraging vector embeddings and cluster-aware caching for fast and scalable performance. Ideal for applications requiring intelligent and accurate text retrieval, such as question answering or information retrieval systems.

Canonical page: https://skillsregistry.net/skills/phaja-semantic-search-project  
JSON: https://api.skillsregistry.net/v1/skills/phaja-semantic-search-project

## Description

Deliver fast, scalable semantic search using vector embeddings and cluster-aware caching for efficient, context-based text retrieval.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-06-18

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Phaja/semantic-search-project)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "phaja-semantic-search-project"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/phaja-semantic-search-project` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/phaja-semantic-search-project/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt