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AirGallery

enhance_image

Enhance image quality: general clean-up, sharpen, denoise or fix lighting. Returns { image }. Cost: 1 credit.

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": "<image>"
    },
    "name": "enhance_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYesImage as a base64 data URI (data:image/png;base64,…) or an HTTPS image URL
enhanceTypeNoKind of enhancement (default general)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden. It does add genuinely useful non-schema context: the response shape "Returns { image }" and the cost "1 credit", which matters for a metered generation endpoint. It says nothing about output resolution, whether the original is preserved, input size limits, or failure/refund behavior, leaving the mutation profile only partially disclosed.

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 short sentences, front-loaded with the action and mode list, then return shape, then cost. Nothing is padded and there is no restatement of the name.

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 image tool with no output schema, disclosing the return shape and credit cost covers the most important unknowns. What is missing is the comparative context against near-duplicate siblings and any constraint on input image size or output resolution, which the schema does not supply either.

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% and includes an enum with a documented default, so both parameters are already fully specified in structured data. The description's mention of clean-up/sharpen/denoise/lighting mirrors the enhanceType enum without adding format, default or interaction semantics.

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 ("Enhance image quality") and enumerates the four concrete operations (clean-up, sharpen, denoise, lighting). It does not distinguish itself from overlapping siblings such as upscale_image, relight_image, photo_repair or dslr_transform, so an agent could hesitate between them.

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

Usage Guidelines2/5

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

Usage is only implied by listing enhancement kinds; there is no explicit when-to-use, when-not-to-use, or named alternative. With siblings like relight_image and photo_repair in the catalog, the absence of routing guidance is a real gap.

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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