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masterkala-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Product reviews

mk_reviews
Read-only

Read MasterKala product reviews and store replies to check quality before recommending a product. Filter by stars and get average, star breakdown, and newest-first results.

Instructions

Read customer reviews of a product (1-5 stars, newest first) with the store's replies and the star breakdown.

Use as a quality check before recommending a product. average and star_counts cover all reviews; count is the number matching stars.

Input Schema

NameRequiredDescriptionDefault
limitNoMax reviews to return, newest first.
starsNoOnly reviews with this many stars (1-5); 0 = all.
full_textNoReturn review and reply text uncut (default cuts at 400 chars).
product_idYesMasterKala product id from mk_search / mk_browse, e.g. 24855.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv0.3.0
    • addedInput schema / properties / full_text
      Added value: +{
+  "default": false,
+  "description": "Return review and reply text uncut (default cuts at 400 chars).",
+  "type": "boolean"
+}
    • removedInput schema / properties / limit / title
      Removed value: -"Limit"
    • removedInput schema / properties / product_id / title
      Removed value: -"Product Id"
    • removedInput schema / properties / stars / title
      Removed value: -"Stars"
    • removedInput schema / title
      Removed value: -"mk_reviewsArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "mk_reviewsDictOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

readOnlyHint=true already establishes the safe-read profile, so the description builds on that by disclosing ordering (newest first), that replies are included, and that text is uncut by default. It also discloses non-obvious semantics: 'average and star_counts cover all reviews; count is the number matching stars' — a subtle aggregate-vs-filter distinction an agent would otherwise get wrong. Pagination and rate-limit behavior remain unstated.

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 short sentences, front-loaded with the core capability and followed by a crisp behavioral footnote. No filler or redundant restatement of the schema.

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?

With no output schema, the description carries the return-value burden and does reasonably well: it names the aggregate fields (average, star_counts, count), notes replies and the star breakdown, and clarifies their scope. The full response shape (field names/types beyond the three named) is still implicit, keeping it just short of complete.

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 coverage is 100%, so the baseline is 3, but the description adds meaning the schema cannot: the interaction between the stars filter and the aggregate fields (average/star_counts unfiltered vs count filtered). The 400-char default cut is repeated from the schema, but the aggregate semantics is genuine added value.

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 (read) and resource (customer reviews of a product) plus scope details: 1-5 stars, newest first, includes store replies and star breakdown. An agent can immediately distinguish this from siblings like mk_product, mk_specs, or mk_search without opening a schema.

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

Usage Guidelines4/5

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

Explicitly frames usage: 'Use as a quality check before recommending a product,' which gives the agent a clear decision context. It stops short of naming alternatives or when-not conditions (e.g., when mk_product's rating summary is enough), so it is clear context without exclusion guidance.

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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