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

Annotations already declare read-only, idempotent, non-destructive. The description adds valuable context beyond annotations: it enumerates the exact data facets (counts, category mix, evidence-ranked, archived, 30-day snapshot volume) and notes it's an API mirror, which helps set expectations about output shape. No contradictions.

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?

Single, well-structured sentence with a clear lead ('One-call') followed by a colon-separated list of contents. Every element is informative and no filler exists. Highly efficient.

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?

Given the tool's simplicity (no params), the description fully covers what the tool provides. An output schema exists, so return values are specified elsewhere. Sibling context and the list of contents make the tool's role clear and complete.

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?

The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter behavior because there are none. The schema is empty and fully covered, and the description adds all necessary context.

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?

Description specifies a unique verb-resource pair: 'One-call ecosystem-level summary' with explicit contents (counts, category mix, leaders, snapshot volume). It distinguishes itself from sibling tools like get_category_ranking by covering the entire ecosystem rather than a specific category. The API mirror reference adds concrete grounding.

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?

Clear context provided: 'ecosystem-level summary' tells the agent when to use it (when needing a broad overview) versus more specific sibling tools. However, it doesn't explicitly name alternatives or state when not to use it, falling short of a 5.

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