ic_research_ask

Active

declared in 1.31.0

Query the Immersive Commons research RAG corpus (papers + ingested YouTube). Returns top-k chunks with similarity scores and source links. The query text is forwarded to a server-side RAG proxy (supercommons2 via Tailnet Funnel) and NEVER logged on the IC side — privacy contract. Use this for literature lookups, finding related work, surfacing citations the floor has already ingested. Args: { question: string (<=500 chars), k?: number (1-50, default 10), sources?: ('paper'|'book')[] (default ['paper']) }. Returns the upstream RAG response shape — typically { results: [{ paper_id, title, similarity, snippet, link }, ...] }. Required scope: research:query.

Parameters schema

{
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "question"
  ],
  "properties": {
    "k": {
      "type": "integer",
      "maximum": 50,
      "minimum": 1,
      "description": "Number of chunks to return. Default 10, max 50."
    },
    "sources": {
      "type": "array",
      "items": {
        "enum": [
          "paper",
          "book"
        ],
        "type": "string"
      },
      "minItems": 1,
      "description": "Which corpora to query. Default ['paper']. Pass ['paper','book'] to span both."
    },
    "question": {
      "type": "string",
      "maxLength": 500,
      "minLength": 1,
      "description": "Natural-language question or keyword query. The proxy embeds and runs top-k retrieval against the corpus."
    }
  }
}

What this tool wraps· 1 endpoint

min confidence0.70 0.50

Data resourceYouTube Data API
Google · media
name mention0.60

Parent server

Immersive Commons

https://github.com/immersive-commons/ic-skills

1/7 registries

View full server →