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video_design_quality_check

Analyzes video design quality across layout, typography, color, motion, and composition. Optionally auto-fixes detected issues to improve visual consistency.

Instructions

Run comprehensive design quality analysis on a video.

Checks layout, typography, color, motion, and composition quality. Can automatically fix issues where possible.

Args: input_path: Absolute path to video file auto_fix: If True, automatically apply fixes strict: If True, treat warnings as errors

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_pathYes
auto_fixNo
strictNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations provided, so the description carries full burden. It mentions 'Run comprehensive design quality analysis' and 'Can automatically fix issues', but does not disclose whether the tool modifies the original file, requires permissions, or has side effects. Behavioral traits are minimally 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?

The description is very concise, front-loading the main purpose, followed by a clear Args section. Every sentence adds value with no redundancy.

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?

Despite having an output schema, the description lacks context on the effect of auto_fix (e.g., whether it modifies the file), and does not clarify distinctions from siblings like 'video_quality_check' or 'video_fix_design_issues'. It is adequate but incomplete for the tool's complexity and sibling set.

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?

With 0% schema coverage, the description adds meaningful explanations for all three parameters: input_path as absolute path, auto_fix enabling automatic fixes, and strict mode for warnings as errors. This compensates well for the lack of schema descriptions.

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?

The description clearly states 'Run comprehensive design quality analysis on a video' and lists specific quality aspects (layout, typography, color, motion, composition). However, it does not differentiate from sibling 'video_quality_check', which may have overlapping functionality.

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 explicit guidance on when to use this tool versus alternatives like 'video_fix_design_issues' or 'video_quality_check'. The description mentions auto-fix capability but does not advise on appropriate scenarios or prerequisites.

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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