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NeuralVerge Business Intelligence

leboncoin Similar Listings

run_leboncoin_listings_similar

Get the 'annonces similaires' recommended for a leboncoin ad (by ID or URL): title, price, attributes, images, location and seller. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
listingYesAd ID or listing URL. e.g. 3188662248
max_itemsNoMax items (up to 100) Default: 10.
start_pageNoStarting page Default: 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

No annotations provided, so the description carries full burden. It usefully discloses the return envelope (title, price, attributes, images, location, seller) and the credit cost model ('1 point per returned record'), which is real behavioral context. However it omits pagination semantics, whether results are live/cached, or failure behavior when an ad has no similar listings.

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?

Single dense sentence that front-loads the action and resource, then enumerates returned fields and the cost model. No filler, no restating of the title.

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

Completeness3/5

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

For a read-only, 3-parameter tool with no output schema and no annotations, the description covers payload shape and cost but leaves pagination behavior and the interaction between start_page and max_items unexplained. Reasonably complete but not fully self-contained.

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 (listing, max_items, start_page) is documented in the schema itself. The description adds the useful note that input may be an ID or URL, but this is already stated in the listing parameter description. Baseline 3 is appropriate.

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?

Specific verb ('Get') and resource ('annonces similaires' / similar listings) for a named platform. Clearly distinguished from siblings like run_kleinanzeigen_listings_similar by the leboncoin scoping and from run_leboncoin_listings by the 'similar' recommendation semantics.

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?

Implied use case is clear (get similar listings for a given ad), but the description never states when to prefer this over run_leboncoin_listings_search or the base run_leboncoin_listings tool, nor any prerequisites. Adequate but with clear gaps.

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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