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

Goes well beyond the annotations by disclosing the asynchronous job pattern (returns job_id immediately, results via scrape_jobs_status), the output language (English), and the billing behavior ('Charged 20 points only when the place is found', full refund on failure). Annotations confirm idempotentHint=true while the schema supplies idempotency_key, and readOnlyHint=false (a job is created) is consistent with the description rather than contradicted.

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 English portion is dense and front-loaded: capabilities first, then inputs, then the async contract, then cost. It is somewhat inflated by a near-full Korean restatement of the same facts, which is redundant for a single-language reader, though it does not obscure the critical leads.

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 still fully covers the call contract: where inputs come from, the immediate job_id return, the required polling tool, the result language, and the cost/refund rule. Nothing an agent needs to invoke and then retrieve results is missing.

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 100%: url, place_id (with pattern) and idempotency_key (with pattern) are all documented in the schema itself. The description only restates the source of place_id/url ('from google_maps_search, or a Google Maps place URL'), adding no new syntax or format guidance beyond what the schema already gives. Baseline 3 applies when the schema carries the parameter burden.

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+resource ('Google Maps place details') and enumerates the exact payload it retrieves: rating, reviews count, star distribution, top reviews, opening hours, busy hours, similar places, photos. It is clearly distinguishable from sibling google_maps_search, which supplies the input rather than the details. An agent can select it without opening a schema.

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 clear operational context: obtain place_id from google_maps_search, or pass a Google Maps place URL, then poll scrape_jobs_status for the result. This routes the agent to both the upstream and downstream sibling. It stops short of an explicit when-not condition (e.g. use search instead of this tool when you only need the place_id), but the sourcing guidance is unambiguous.

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