get_interview_guides

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

No annotations are provided, so the description carries the full burden. It discloses the return behavior ('full guide content (markdown)') and the filtering rule ('for each section that has one'), which is sufficient for a simple read-only getter. It does not mention error cases, but that is a minor gap.

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 compact and front-loaded: a clear one-sentence purpose, a short return clarification, a usage hint, and an args block. Every sentence earns its place with no filler.

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?

The tool is simple with one parameter and an output schema. The description covers purpose, return content, and timing. It does not need to explain output schema details since the output schema exists, and the usage guidance is sufficient for tool selection.

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 0%, but the description compensates by explaining study_id as 'The unique identifier of the study.' This adds meaning beyond the schema's type/title, and with only one parameter, this is adequate.

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 begins with a specific verb and resource: 'Get all interview guides for every section in a study.' It clearly identifies the scope (all sections), the object (interview guides), and differentiates from siblings like get_sections or generate_guide by mentioning the full guide content in markdown.

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?

Provides clear usage context: 'Use this after study creation to see the AI-generated interview guides.' This tells the agent when to invoke the tool, though it does not explicitly state when not to use it or name alternative tools for exclusions.

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