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dialogbrain

by io.github.saloprj
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images_search

Read-onlyIdempotent

Searches images in this workspace by visual content using vector embeddings (Voyage multimodal-3). Pass a text description; returns ranked file_ids with cosine scores and presigned download URLs. Up to 50 results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax number of results.
queryYesText description of what you're looking for (3-4000 chars).
mime_typeNoOptional — restrict to a specific image MIME (e.g. "image/png"). Filter is applied after RAG (same caveat as collection_id).
in_workspaceNoRun this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.
collection_idNoOptional — restrict to images attached to this collection. Filter is applied after RAG, so you may get fewer than `limit` results; pass a larger limit to broaden if needed.
score_thresholdNoMinimum cosine similarity (0.0 returns all, higher = stricter).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / in_workspace
      Added value: +{
+  "description": "Run this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.",
+  "type": "integer"
+}
  2. Added
  3. Removed
  4. First observed

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover readOnly, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: the embedding model (Voyage multimodal-3), the return structure (ranked file_ids, cosine scores, presigned download URLs), and a result cap of 50. It does not mention auth requirements or pagination, but the additions are useful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three compact sentences cover purpose, invocation, and return format. The information is front-loaded, and every sentence contributes meaning without filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description appropriately discloses the return format and result limit. It omits some caveats that live in the schema (post-RAG filtering, workspace override) and never routes to alternatives, but it covers what an agent minimally needs to call the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema documents all six parameters in detail. The description only restates 'Pass a text description' and 'Up to 50 results', adding little meaning beyond what the schema already provides, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Searches images') along with scope ('in this workspace by visual content using vector embeddings'). It does not explicitly distinguish itself from sibling tools such as vision_query or search_files, so no sibling differentiation is present.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage: pass a text description to search images. No when-to-use or when-not-to-use guidance is provided, and no alternatives such as vision_query or search_files are named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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