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generate_content
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Generate new prose from a natural-language prompt. Use project context like documents or characters to steer content. Specify target length for tailored output.

Instructions

Generate new prose from a natural-language prompt and return the generated text, optionally steered by project context (a document, characters, or a target style) and a desired length. This creates fresh text and does not modify any document. Use enhance_content to improve existing text instead, or analyze_document to critique it. Calls an external AI model and requires an AI provider key (ANTHROPIC_API_KEY, OPENAI_API_KEY, or OPENROUTER_API_KEY); without one a placeholder is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lengthNoApproximate target length in words. Default 500.
promptYesNatural-language instruction describing the content to generate.
contextNoOptional project context to steer generation.
Behavior4/5

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

Description adds that the tool does not modify documents (consistent with annotations) and details external AI model dependency and fallback behavior (placeholder).

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?

Three concise sentences, front-loaded with purpose, each sentence adds essential information.

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?

Covers purpose, usage, dependencies, and side effects. Could mention return format, but returning generated text is implied.

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 coverage is 100%, but description adds context on how 'context' and 'length' steer generation, adding minimal value beyond 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?

Clearly states it generates new prose from a prompt, distinguishes from enhance_content and analyze_document.

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

Usage Guidelines5/5

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

Explicitly says when to use (generate new text) and when not (use enhance_content/analyze_document for existing text). Also mentions AI provider key requirement.

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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