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Glama

Seller and their ads

dv_seller
Read-onlyIdempotent

Inspect the seller behind a Divar ad: see if they are personal or business, view their business card and brand token, and list their other ads to judge if they are a dealer.

Instructions

The seller behind an ad: how many personal and business ads they have, the business card (name, brand_token) and their ads.

Use to judge a seller (one flat or fifty cars?) and to list their other ads. For a dealer's whole page call dv_dealer with the brand_token (dv_post does not give one). A personal seller has no business card (seller_kind). No phone number or identity is exposed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax of the seller's other ads to return.
tokenYesAd token: the last part of divar.ir/v/<slug>/<token> or `token` of a search result, e.g. 'gaRPIP2m'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds genuine context beyond them: the privacy posture ('No phone number or identity is exposed') and the data-shape caveat that a personal seller has no business card (`seller_kind`).

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 outputs, then usage, then caveats. The parentheticals ('one flat or fifty cars?') carry real semantic signal rather than filler, though the sentence count is slightly higher than strictly needed.

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?

No output schema exists, so the description must carry return-value meaning, and it does: ad counts, business card fields, and the ad list, plus the seller_kind caveat. Nothing an agent needs to call this correctly is missing.

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 description coverage is 100%, so both input params (token, limit) are fully documented in the schema. The description mentions brand_token and seller_kind, but those are output fields rather than inputs, so it adds little input-parameter meaning beyond the schema. Baseline 3.

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 resource ('the seller behind an ad') and enumerates the concrete outputs: personal/business ad counts, the business card (name, brand_token), and their ads. It also differentiates itself from siblings by naming dv_dealer and dv_post, so an agent can place it precisely.

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

Usage Guidelines5/5

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

Explicitly states the use case ('judge a seller... and list their other ads') and routes to the alternative: 'For a dealer's whole page call dv_dealer with the brand_token (`dv_post` does not give one)'. The when-to-use and the fallback are both spelled out.

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