generate_prompt

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

With no annotations provided, the description carries full burden. It describes the transformation behavior and template support, but lacks details on output format, potential limitations (e.g., length constraints), error handling, or performance characteristics. It provides some context about workspace alignment but doesn't fully compensate for the missing annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections: purpose statement, usage bullet points, template list, and important note. It's appropriately sized for a 5-parameter tool, though the template list could be more concise. Every sentence adds value, but minor trimming is possible.

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

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

For a 5-parameter tool with no annotations and no output schema, the description provides good purpose and usage context but lacks details about the transformation output, error cases, or behavioral constraints. It's adequate for basic understanding but leaves gaps about what the tool actually produces.

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

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

Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds minimal value beyond the schema: it mentions template types and workspace context importance, but doesn't explain parameter interactions or provide additional semantic context. Baseline 3 is appropriate given the comprehensive schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Transform a raw idea into a well-structured, actionable prompt optimized for AI assistants.' It uses specific verbs ('transform', 'optimize') and distinguishes from sibling tools like 'analyze_prompt' and 'refine_prompt' by focusing on creation from scratch rather than analysis or refinement.

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

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

The description provides explicit usage scenarios: 'Create a new prompt from scratch', 'Structure a vague idea into a clear request', and 'Generate role-specific prompts'. It also implicitly distinguishes from siblings by not mentioning analysis or refinement, and includes an 'IMPORTANT' note about when to provide workspace context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.