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

With no annotations present, the description carries the full behavioral burden and does it exceptionally well: fuzzy matching, ranking, ambiguity flags, read-only dimension-table access, and concrete edge-case behavior like consolidated_city, typo, and place_note handling are all disclosed.

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 front-loaded with the core purpose and then layers in necessary detail. It is dense and slightly run-on, but every sentence adds genuinely useful information about behavior or matching semantics rather than repeating the name or schema.

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 complexity and the presence of an output schema, the description covers nearly everything needed: purpose, kind semantics, ambiguity, edge cases, and a user-facing instruction about place_note. The only incomplete piece is the `limit` parameter's effect on candidate ranking.

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 richly explains `kind` and `query`, including the ambiguous 'Fulton' example, but never describes `limit` even though it appears in the schema. This is a minor gap for an optional integer parameter.

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 opens with a specific verb and resource: 'Resolve a place or demographic NAME or CODE to its stable keys + labels', and clarifies that it is the right way to produce filter values. The Fulton-as-county vs Fulton-as-district example makes the tool's scope and kind-sensitivity unmistakable.

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 says to use this when converting a name/code into stable filter keys, and explicitly warns that guessing a code incorrectly returns an empty query_dataset page. It does not name sibling alternatives explicitly or state when not to use it, but the intended context is clear.

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