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generate_themes

Generate new content themes using AI from source text or files. Set count and custom instructions for tailored suggestions.

Instructions

Generate new content themes using AI. Waits a short grace window for generation to finish; if it's still running server-side after that, returns a 'generating' status instead of blocking — call list_themes a few seconds later to retrieve the new themes. Deducts credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of themes to generate
inputNoSource text or file path to derive themes from
brandIdNoBrand ID (uses active brand if omitted)
instructionsNoCustom instructions, e.g. 'Focus on startup growth'
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently explains the asynchronous behavior: waits a short grace window, returns a 'generating' status if still running, and does not block. It also discloses that credits are deducted, which is a critical side effect for an agent to know before invoking.

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 concise and well-structured: two sentences that first state the purpose, then provide essential behavioral details and follow-up instructions. Every sentence adds value, and there is no redundant or irrelevant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is complete for a tool with no required parameters and no output schema. It explains the asynchronous return behavior, the need to later call list_themes, and the credit deduction. This gives an agent enough context to use the tool correctly and handle the result.

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 all parameters have descriptions in the schema. The tool description itself does not add further elaboration on parameter semantics. Since the schema already does the heavy lifting, the baseline score of 3 is appropriate.

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's purpose: 'Generate new content themes using AI.' This is a specific verb+resource combination that distinguishes it from related sibling tools like list_themes, edit_theme, and delete_theme. The scope is unambiguous.

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 clear context for usage: it generates themes and then instructs to 'call list_themes a few seconds later to retrieve the new themes.' This gives a sequential workflow. However, it does not explicitly mention alternatives or when not to use this tool, though the follow-up reference to list_themes implies the intended flow.

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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