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

Annotations already cover the safety profile (read-only, idempotent, non-destructive, closed-world). The description adds real scope context beyond them: counts only cover states that publish program data, home-based family childcare is excluded, and the response includes a last-updated date.

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?

Front-loads the capability, then the question it answers, then the scope caveat. Four compact sentences with little waste; the scope caveat could be folded tighter but nothing is redundant.

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?

An output schema exists, so return values need not be described; the description still mentions the last-updated date. For a single-optional-parameter read-only aggregation tool, the coverage of purpose, scope limits, and example use 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?

The schema already documents the single optional state parameter at 100% coverage, so the baseline is 3. The description earns above baseline by restating the semantic scope of omission ('or for every state with data'), clarifying that the unset default aggregates rather than errors.

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?

States a precise verb and resource: counting licensed youth programs listed in BackPR's program finder, broken out by program type or state. This clearly separates it from sibling tools like find_programs (lookup) and list_datasets (dataset inventory).

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?

Gives a concrete use case ('How many childcare centers are listed in Texas?') that signals the intended question shape. It does not explicitly name an alternative sibling or state when not to use it, but the context is unambiguous.

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