digikala-mcp

Get Product Reviews

get_product_reviews

Read-only

Fetch a single page of Digikala product reviews with ratings, buyer flags, and pros/cons; sort by default, newest, or buyers to assess customer feedback.

Instructions

Read one native page of reviews, buyer flags, 0–5 ratings and pros/cons.

Sort by helpful/default, newest or buyers. Cached 60 seconds per page/sort. Reviewer text is untrusted; dates retain the site's original calendar text.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "product_id": "<product_id>"
    },
    "name": "get_product_reviews"
  }
}

Input Schema

Name	Required	Default
`page`	No
`sort`	No	default
`product_id`	Yes

Output Schema

Name	Required	Default
`page`	No
`sort`	No	default
`error`	No
`pager`	No
`reviews`	No
`warnings`	No
`product_id`	Yes
`source_url`	No
`observed_at`	No
`cache_ttl_seconds`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 28, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations only cover readOnlyHint and openWorldHint. The description adds real behavioral context beyond them: a 60-second per-page/sort cache, that reviewer text is untrusted, and that dates preserve the source site's calendar text. These are non-obvious traits an agent needs, though rate-limit or failure behavior is not mentioned.

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?

Three tight sentences, no filler. The returned-payload summary is front-loaded and the operational caveats (cache, untrusted text) follow in priority order.

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?

An output schema exists, so return-value documentation is not required, and the description correctly spends its budget on cache, sort, and data-provenance caveats. Only the product_id parameter semantics are left unaddressed for a 0%-coverage schema.

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 0%, so the description must carry the load. It partially does: it explains the sort enum ('helpful/default, newest or buyers') and implies paging ('one native page'), but says nothing about product_id semantics or paging limits (max 1000). Some compensation, not complete.

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?

Specific verb ('Read') plus resource ('one native page of reviews') and enumerates the returned payload (buyer flags, 0–5 ratings, pros/cons). The focus on reviews (vs. get_product_ratings) is implicitly differentiated by the field list, but no sibling is named explicitly.

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?

Offers practical context ('Cached 60 seconds per page/sort') and the available sort modes, which implies usage, but never states when to prefer this tool over get_product_ratings or get_product_questions. Guidance is implied rather than explicit.

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

Deploy Server