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asset_ingest_external

Ingest externally generated images from tools like Midjourney or Ideogram, then automatically run matting, vectorization, and tier-0 validation to prepare assets for multi-platform bundling.

Instructions

Ingest an image the user generated in an external tool (Midjourney, Nano Banana, Ideogram web, Recraft, Flux Playground, etc.) and run the matte → vectorize (where applicable) → tier-0 validation pipeline. The round-trip endpoint for external_prompt_only mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_pathYesAbsolute path to the locally-saved image.
asset_typeYes
brand_bundleNo
expected_textNo
vectorNo
transparentNo
output_dirNo
Behavior2/5

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

The description outlines the pipeline steps but lacks details on side effects, permissions, what happens to the input image, or output format. Annotations are minimal, so description should compensate but does not.

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, concise and front-loaded, but could better structure the pipeline steps and parameter context.

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 7 parameters, low schema coverage, no output schema, and a multi-step pipeline, the description is incomplete. It omits parameter semantics and does not explain 'tier-0 validation' or output.

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 14%, and the description adds no parameter explanations beyond the pipeline mention. It does not describe brand_bundle, expected_text, vector, transparent, or output_dir.

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 clearly states the tool ingests externally generated images and runs a specific pipeline (matte, vectorize, validation), distinguishing it from sibling generation tools.

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?

The description provides context by listing external tools and mentioning 'round-trip endpoint for external_prompt_only mode', but does not explicitly state when not to use it or name alternatives.

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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