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ingest_generated_images

Accept a slug and asset-key image map to normalize generated illustrations, center-crop them to 1280x960 4:3 landscape, and save each as PNG and WebP for storybook pages.

Instructions

Step 3: After generating illustrations (via subagents or image tools), pass a dictionary mapping asset keys (e.g. {"cover": "/path/to/img.jpg", "page-01-reality": "..."}) to normalize, center-crop to 1280x960 (4:3 landscape), and save both .png and .webp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
image_mapYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full load, and it does disclose the meaningful behavioral trait: images are center-cropped (a lossy operation) to a fixed 1280x960 4:3 frame and written out in two formats. It does not say where files land, whether existing files are overwritten, or how invalid keys are handled, leaving some gaps.

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?

A single dense sentence that front-loads the step context and the input format, then lists the transformations. The inline example removes ambiguity at no real cost in length; nothing is wasted.

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?

An output schema exists, so return values need not be described, and the description covers input shape and the processing pipeline adequately for a 2-parameter write tool. Remaining gaps around output file location and overwrite/missing-key behavior are minor but real.

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

Parameters4/5

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

Schema description coverage is 0% and the schema only shows an untyped string map, so the description must compensate — and it does, defining image_map as asset-key-to-path with a concrete example including keys like "cover" and "page-01-reality". The required `slug` parameter is never explained, which keeps this from being a 5.

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

Purpose5/5

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

The description names a specific verb+resource (ingest generated images) and goes further to state exactly what happens to them: normalize, center-crop to 1280x960, and save as .png and .webp. No sibling tool in the list deals with image ingestion, so there is no ambiguity to resolve.

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

Usage Guidelines4/5

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

"Step 3: After generating illustrations (via subagents or image tools)" gives clear sequencing and prerequisite context, telling the agent this runs downstream of image generation. It stops short of naming explicit exclusions or alternatives, so it is not a full when/when-not statement.

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