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image_batch_edit

Apply one prompt to edit up to 10 local images in sequence, stopping on first failure with a report of completed files.

Instructions

Edit up to 10 local images sequentially with one prompt. Each image uses paid quota. Stops on first failure and reports completed files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNo1024x1024
modelNo
promptYes
api_keyNo
qualityNo
image_pathsYes
response_formatNob64_json

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.0
    • addedInput schema / properties / api_key
      Added value: +{
      +  "maxLength": 200,
      +  "minLength": 1,
      +  "type": "string"
      +}
  2. First observedv0.1.0

TDQS

B3.2/5.0
Behavior4/5

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

Description adds important behavior beyond annotations: sequential processing, paid quota consumption, stop-on-first-failure, and reporting of completed files. This complements the readOnly=false annotation without contradicting it. Could still note API-key/auth requirements more explicitly, but the added context is strong.

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?

One dense sentence front-loads the core capability, then adds cost and failure behavior without filler. Every clause adds new information.

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

Completeness2/5

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

With no output schema and zero parameter descriptions, the tool needs more context to be invoked correctly—especially since optional fields like api_key, model, quality, and response_format are unexplained. 'Reports completed files' is too vague about the return payload; missing parameter semantics make the definition incomplete.

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 description coverage is 0%, so description must carry parameter meaning. It only clarifies image_paths (up to 10 local images) and prompt ('one prompt'), while leaving size, model, api_key, quality, and response_format unaddressed. This is insufficient for 7 parameters.

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?

Description uses specific verb 'Edit' and resource 'local images' with a hard cap of 10, making the batch intent clear. It does distinguish from a single-image edit by quantity, but never names sibling tools like image_edit or image_multi_reference, so the differentiation is implied not explicit.

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?

No sentence tells the agent when to choose this tool over image_edit, image_generate, or image_multi_reference. The batch/10-image wording implies a multi-image use case, but there are no explicit exclusion criteria or alternative references.

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