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

Annotations already signal non-read-only, non-idempotent, and non-destructive behavior. The description adds that the operation persists data and only targets missing sections, which is useful. However, it does not clarify what happens on repeated calls, how the idempotency_key should be used, or whether execution is asynchronous, leaving some behavioral ambiguity.

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 one tight sentence with no filler. The primary action, target resource, and scoping condition are all front-loaded, so an agent can absorb the core meaning at a glance.

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?

While the output schema exists and the high-level purpose is clear, the description leaves required parameter semantics unexplained, especially the difference between project_id and validation_project_id and the meaning of idempotency_key. For a tool with 0% schema description coverage and two required IDs, this is a meaningful completeness gap.

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%, so the description must compensate. It provides meaningful context for the 'sections' parameter by naming market, competitor, and market-size categories, but it does not explain the distinction between the two required IDs (validation_project_id vs project_id) or the purpose of idempotency_key. Those gaps are significant for correct invocation.

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 names a specific action ('generate and store') and a specific resource ('market, competitor, or market-size analysis sections') scoped to a private validation project. This is plainly distinct from sibling tools like validation.create_project, validation.get_project, and validation.list_projects, so an agent can select it without deep schema inspection.

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 word 'missing' gives a practical condition: use this tool when analysis sections are absent and need to be filled in. It implies a when-not-to-use case (sections already present), but it does not explicitly name alternatives or state exclusions, so it stops short of a fully explicit routing guide.

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