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BrightLocal by Cotlet

Get a Local Search Grid report

get_local_search_grid_report
Read-onlyIdempotent

Read a location's Local Search Grid: the Google Maps rank at each grid point, and competitors. Returns the grid (size, points, distance, center), the average rank over all keywords, each keyword's latest run (average rank, points ranked 1-3, 4-10, 11+), and for one keyword and run (the first keyword and the latest run unless given) the rank at every grid point and the top 10 competitors. A location without a Google Business Profile has no grid: report is null and note says what to set up.

Input Schema

NameRequiredDescriptionDefault
run_idNoA run from the keyword's `runs`. Default: the latest.
keywordNoA keyword of the report. Default: the first.
location_idYeslocation_id from list_locations.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds real behavioral context beyond them: the default scope of the selected keyword/run and the important failure mode where a location without a Google Business Profile returns `report: null` with an explanatory `note`.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the resource and its payload, then progressively narrows to the selected keyword/run and finally the null case. It is dense and mostly earned, though the long chain of clauses in the middle sentence requires a second read.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description compensates by enumerating the returned structure: grid metrics, average rank, per-keyword run stats, per-point ranks, and top 10 competitors. With the null-and-note edge case documented, an agent has everything needed to call this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and each parameter already carries a description including its default, so the description only restates the default rule ("the first keyword and the latest run unless given"). It adds no format, range, or identifier-provenance detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Read a location's Local Search Grid: the Google Maps rank at each grid point, and competitors" names a specific verb and resource and enumerates the returned data. It is clearly distinct from the sibling list_local_search_grid_reports by being a single-location report, though it never explicitly names that sibling to reinforce the split.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: the description gives the defaults ("the first keyword and the latest run unless given") and the GBP prerequisite case, which tells the agent how to call it. It never says when to reach for this versus list_local_search_grid_reports or get_rank_tracker_report, so the choice is left to inference from the name.

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

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