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bailian-tools-mcp

bailian-tools-mcp

by niradler
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

Search by image (Model Studio)

image_search

Find visually similar images or trace an image's origin from a public URL using reverse image search to identify sources and related visuals.

Instructions

Reverse image search: find visually similar images or trace where an image comes from, using Model Studio's image_search tool. 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": {
      "image_url": "<image_url>"
    },
    "name": "image_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNoOptional guidance, e.g. 'find where this photo was published'.
image_urlYesPublic http(s) URL of the image to match.
max_output_tokensNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose a genuine behavioral trait: billing against the Model Studio plan (~$10/1k web searches, Singapore rate) plus a bulk-use caution. That is valuable and non-obvious cost context, but it says nothing about result shape, latency, or what happens on failure to fetch the image.

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

Conciseness4/5

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

Two sentences, front-loaded with the capability and followed by the cost caveat, with no filler. The clause "using Model Studio's image_search tool" mildly restates the name and title but is not enough waste to lower further.

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 tool with no annotations and no output schema, the definition covers cost and intent but leaves the return side entirely implicit — an agent cannot tell whether it receives image URLs, source pages, or match scores. Given three parameters with one undocumented, this is adequate but incomplete.

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 coverage is 67%, so image_url and query are already documented inline; the description adds no syntax or format meaning beyond that. The third parameter, max_output_tokens, is undocumented in both places, and the description does not help an agent reason about how per-search billing interacts with it.

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?

"Reverse image search: find visually similar images or trace where an image comes from" states a specific verb and resource with two concrete use modes. It is distinguishable from the sibling list by the word "image" and the input being an image rather than a text query, though it never explicitly contrasts itself with text_to_image_search.

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?

The purpose implies when to reach for it (you have an image and want matches or provenance), and "ask before bulk use" gives a real precondition for high-volume calls. However, there is no explicit when-not guidance and no named alternative for the closely adjacent text_to_image_search sibling.

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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