Alphakdeps.io is experimental and evolving — the registry and packages may change or reset.
Toolkdeps asset

kdeps-tools-embedding_search

v1.0.0

Search for documents semantically similar to a query in the local embedding database. Returns ranked results with similarity scores. Requires: query (natural language search query), collection (name of the document collection). Optional: limit (max results, default 5).

set tools / shelf rag

LLM context: ~142 tokens when loaded (prompt or tool definition)

Where it runs

Part of the tools set, used in workflow and agent mode. What the model is told about each built-in tool: its description, usage notes and parameters. kdeps runs the tool itself.

  1. the agent loop builds the request
  2. the tool definitions are sent to the modeltools/embedding_search
  3. the model calls a tool
  4. kdeps runs it
  5. the result goes back to the model

Loaded by: kdeps (agent loop), /update, /settings, kdeps run, kdeps install, kdeps list, kdeps uninstall, kdeps update

In the code: kdeps (agent loop)agent.RegisterBuiltinToolsagent.definedAs

Install

A kdeps asset: installed with the first-run profile that includes its set, or the first time a command needs it, and updated without a new release.

kdeps install tools/embedding_search

Pin a version with kdeps install tools/embedding_search@<version>.

Contents

Search for documents semantically similar to a query in the local embedding database. Returns ranked results with similarity scores. Requires: query (natural language search query), collection (name of the document collection). Optional: limit (max results, default 5).

ParameterTypeDescription
collection *stringName of the document collection to search
limitnumberMaximum number of results. Default: 5
query *stringNatural language search query

Versions

VersionPublishedStatus
1.0.010/11/2026active

Details

Author
kdeps
License
Apache-2.0
Latest Version
1.0.0
Published
10/11/2026

Tags

kdepstool