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qa_check

Run a quality control check on generated images to evaluate accuracy, consistency, and composition, returning a structured verdict with scores and issues.

Instructions

Run a quality-control check on a generated image and return a structured verdict.

Call this immediately after generating an image, before showing it to the user.

Parameters:

  • image_path: Absolute path to the generated image to review.

  • reference_images: Optional list of reference image paths to compare against (e.g. character/style references). Up to 3 are used.

  • character_rules: Free-text rules the image must follow, e.g. "The pilot has NO eyebrows; the jacket has horizontal stripes."

  • style_notes: Free-text description of the expected visual style.

  • scene_type: One of solo, portrait, battle, combat, group, action, interview. Adjusts composition expectations (e.g. portraits may face camera).

  • pass_threshold: Minimum overall score (0-1) to pass. Default 0.7.

Returns a dict with: passed (bool), overall_score, character_accuracy, style_consistency, quality_score, composition_score (all 0-1), issues (list of {severity, category, description, recommendation}), should_regenerate (bool), notes, and model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_pathYes
scene_typeNogroup
style_notesNo
pass_thresholdNo
character_rulesNo
reference_imagesNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains the return value structure and parameter behavior (e.g., reference_images limited to 3), but does not disclose possible side effects, error handling, or auth requirements. It is adequate but not fully transparent.

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?

The description is moderately long but well-structured, with a clear purpose statement followed by parameter details. It is front-loaded with the core action. Minor redundancy could be trimmed, but overall it is efficient.

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?

Given 6 parameters, no output schema, and no annotations, the description covers the return dict fields and parameter defaults. However, it lacks information about validation rules, error handling, and the allowed enum values for scene_type (though a sibling tool exists). It is somewhat incomplete for a complex tool.

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

Parameters5/5

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

With 0% schema description coverage, the description thoroughly explains all 6 parameters, including types, defaults, and usage examples (e.g., character_rules example, scene_type with composition expectations). This adds significant meaning beyond the bare schema.

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 'Run a quality-control check on a generated image and return a structured verdict' and specifies when to call it ('immediately after generating an image, before showing it to the user'). This provides a specific verb+resource and distinguishes it from the sibling tool 'list_scene_types'.

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 explicitly advises 'Call this immediately after generating an image, before showing it to the user,' which is clear usage guidance. However, it does not explicitly state when not to use the tool or mention alternatives, so it loses one point.

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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