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analyze_intent

Parses creative prompts into structured intent dimensions, detecting camera language, motion, lighting, style, and mood signals, while identifying gaps and suitable models.

Instructions

Parse a creative prompt into structured intent dimensions.

Returns: detected camera language, motion, lighting, style, mood signals, identified gaps, and which models suit the current signals best.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mediumNo"image", "video", or "auto" (default, auto-detected)auto
promptYesRaw creative text (rough idea or full prompt — both work)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It only lists return values and does not mention side effects, permissions, rate limits, or destructive potential. This lack of guidance reduces transparency.

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 two sentences: the first states the purpose, the second lists the returns. It is front-loaded, concise, and contains no superfluous words.

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?

The description provides purpose and return components, and an output schema exists to detail the return structure. It is mostly complete, though it could briefly differentiate from siblings or note prerequisites.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already explains both parameters. The tool description does not add new parameter-level details beyond the schema, resulting in a baseline score of 3.

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 the verb 'Parse' and resource 'creative prompt into structured intent dimensions'. The return list provides a specific outcome. However, it does not explicitly differentiate from sibling tools like 'score_prompt' or 'enhance_prompt', so score 4 rather than 5.

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

Usage Guidelines3/5

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

The description implies usage when a user wants to analyze a creative prompt's intent, but it does not provide explicit when-to-use, when-not-to-use, or alternative tools. This makes it adequate but not strong.

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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