bailian-tools-mcp

Text-to-image search (Model Studio)

text_to_image_search

Find images on the web from a text description to support visual answers, illustration hunting, and image recommendations.

Instructions

Find images on the web from a text description using Model Studio's web_search_image tool. Use for visual answers, illustration hunting and image recommendations. Billed to your Model Studio plan (~$10/1k web searches in Singapore) — ask before bulk use.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "text_to_image_search"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Description of the images to find.
`max_output_tokens`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 13, 2026

TDQS

A3.5/5.0

Behavior4/5

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

With no annotations to lean on, the description still volunteers the most decision-relevant behavior: it is billed to a Model Studio plan at roughly $10/1k searches in Singapore, and bulk use should be confirmed first. It also discloses the underlying provider dependency. It stops short of describing what the results look like or any rate/limits beyond cost.

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?

Two sentences, purpose first, cost/risk second, with no filler. The pricing parenthetical is dense but earns its place because it changes agent behavior around bulk calls.

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

Completeness3/5

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

For a two-parameter read-style tool with no output schema, the description covers purpose, provider, and cost caution adequately. It is incomplete on the one ambiguous parameter and on what a result contains, which matters because there is no output schema and no annotations to fill those gaps.

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

Parameters2/5

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

Schema coverage is only 50%: 'query' is documented in the schema, but 'max_output_tokens' is undocumented in both places, and it is a genuinely confusing name for an image search tool (tokens of what — the query, the response, the number of images?). The description adds no parameter meaning at all, so it fails to compensate for the coverage gap.

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?

The description states a specific verb and resource ('Find images on the web from a text description') and even names the underlying provider tool (web_search_image). However, it never differentiates itself from the sibling 'image_search', which reads as near-identical in purpose, so an agent cannot route between them from this text alone.

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?

It gives positive usage contexts ('visual answers, illustration hunting and image recommendations') and a caution to 'ask before bulk use', which implies a cost-sensitive workflow. There is no explicit when-not-to-use guidance and no named alternative, which is a real gap given the ambiguous 'image_search' sibling.

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

Deploy Server