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

Annotations already declare readOnlyHint=true, so the description doesn't need to restate that. The description adds useful behavioral context: the order of questions, the structure of each question (id, type, options, condition), and the fallback behavior for skipped questions. This goes beyond the schema and annotations, though it doesn't detail the exact response format or pagination (likely not needed for a single questionnaire).

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 concise and well-structured: it explains the output structure, the question format, the conditional logic, and the downstream usage in a few sentences. Every sentence adds value, and the most important information (what the tool returns) is front-loaded.

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 simple read-only tool with one parameter and no output schema, the description is quite complete. It covers the question structure, the ordering, the conditional behavior, and the next step (generate_spec). The only minor gap is that it doesn't explicitly state the response format (e.g., JSON array), but the description of question fields implies it. Given the low complexity, this is sufficient.

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 coverage is 100%: the only parameter 'type' is fully described with an enum of project types. The description adds context about what the parameter represents (project type) and how it affects the returned questions, but the schema already provides the enum and description. Baseline 3 is appropriate since the schema does the heavy lifting.

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: retrieving the questionnaire for a project type, with a specific structure (universal questions first, then type-specific ones). It distinguishes itself from siblings by mentioning the downstream use (pass answers to generate_spec) and the required fields, making it clear this is a read-only questionnaire retrieval tool.

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 clear context on when to use this tool: when you need the questions for a project type. It also gives guidance on what to do after retrieving the answers (pass to generate_spec) and notes that only project_name and project_description are required. However, it doesn't explicitly state when NOT to use it or name alternatives like list_project_types, though the context signals show siblings that are clearly different.

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