generate_guide

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

Discloses the 30–90 second latency and directs warning the user. Details the post-generation workflow (present guide, use update_interview_guide for changes) and return format (markdown). With no annotations, this fully describes expected behavior.

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?

Well-structured with clear sections: purpose, prerequisites, latency, post-generation guidance, return, and args. All sentences add value; front-loaded with the core purpose.

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?

Covers prerequisites, runtime behavior, follow-up steps, and return format. With only two simple parameters and a straightforward outcome, this is adequate for an agent to execute correctly.

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 has no descriptions and coverage is 0%, so description compensates by defining study_id and section_id as unique identifiers. Adds an Args section with plain-language definitions, though it doesn't provide examples or where to locate these IDs.

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?

Clearly states it generates an AI-powered interview guide for a section, using study objectives, persona, and section config. Distinguishes from update_interview_guide and get_interview_guides by its generation-specific action.

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?

Explicitly lists prerequisites (objectives, persona, section name/description) and directs users to update_study_details and update_section if unmet. Also instructs to use update_interview_guide for changes instead of regenerating, providing clear when-to-use vs alternatives.

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