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NeuralVerge Business Intelligence

leboncoin Locations Search

run_leboncoin_locations_search

Resolve a French place name or postcode into leboncoin location objects: label, city, zipcode, department/region id and coordinates. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYesSearch term. e.g. Bordeaux
max_itemsNoMax items (up to 50) Default: 25.
start_pageNoStarting page Default: 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are present, so the description carries the full behavioral burden. It usefully discloses a cost trait ('1 point per returned record') and the output fields, but omits read-only safety, permission requirements, pagination behavior, and rate limits.

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

Conciseness5/5

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

Two tight sentences with no wasted text. The purpose is front-loaded, followed by output fields and cost.

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

Completeness4/5

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

For a low-complexity location resolver with no output schema, the description lists the returned location fields and notes the per-record point cost. It lacks routing guidance, but is otherwise complete enough to call correctly.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful semantics by clarifying that the keyword accepts a French place name or postcode, beyond the schema's generic 'Search term. e.g. Bordeaux'.

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

Purpose5/5

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

States a specific verb ('Resolve') and resource ('French place name or postcode into leboncoin location objects'), then lists the returned fields. This is clearly distinct from the listing, category, and seller search siblings.

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

Usage Guidelines2/5

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

Provides no when-to-use guidance, no prerequisites, and no mention of alternatives. An agent gets no help deciding between this and the other leboncoin search tools.

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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