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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=true, so safety and idempotency are covered. The description adds nothing about the open-world implication — that resolution likely hits an external geocoding service, what happens to unresolvable or ambiguous locations, or whether results are cached. With annotations carrying the safety profile, this is adequate but thin.

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?

Two sentences, front-loaded with the transformation and followed by downstream use cases. No filler, though the second sentence is more marketing framing than operational guidance.

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?

With no output schema, the description helpfully enumerates the returned fields (city, state, country, ISO codes, latitude, longitude), which is real value. It still doesn't clarify cardinality — whether multiple input locations or a parsed JSON blob yield one resolved object or a list — which leaves a meaningful gap for a tool accepting arrays and free-text blobs.

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% and both parameters carry detailed descriptions including an example object shape and the json_text extraction behavior, so the description need not restate them. It adds no syntax or format guidance beyond the schema, which is the baseline case for full coverage.

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 uses a specific verb ('Converts') and enumerates the resource and transformation target ('partial or informal location text' into city, state, country, ISO codes, lat/long). This is clearly distinguishable from siblings like normalize_candidate_data or classify_job_zone, though it never names an alternative explicitly.

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?

Downstream uses are named ('enables radius-based candidate and job search', 'workforce planning analytics'), which implies when the tool is useful. However, there are no explicit conditions, prerequisites, or exclusions — nothing says when to call this versus normalize_hr_data_with_lov or normalize_candidate_data, which also touch location-bearing data.

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