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asalbanoo-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Filters of a category or brand

ab_filters
Read-onlyIdempotent

Retrieve attribute filters—volume, hair/skin type, gender, origin—with in-stock counts for a category or brand. Use with ab_browse to narrow products by size or type.

Instructions

List the attribute filters of a category or brand (volume, hair/skin type, gender, origin) with in-stock counts.

Use before ab_browse for a size or type: pass {attribute: [value, ...]} as its filters.

Input Schema

NameRequiredDescriptionDefault
brandNoBrand slug from ab_brands, e.g. 'graph' or 'la-roche-posay'.
categoryNoCategory slug from ab_categories, e.g. 'hair-shampoo' or 'sunscreen'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.3.0
    • removedInput schema / properties / brand / title
      Removed value: -"Brand"
    • removedInput schema / properties / category / title
      Removed value: -"Category"
    • removedInput schema / title
      Removed value: -"ab_filtersArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "ab_filtersDictOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuine context beyond that: the response carries in-stock counts and the returned attributes are directly reusable as ab_browse filters. Pagination/rate-limit behavior is not mentioned, keeping it below a 5.

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: the first defines the resource and its output fields, the second front-loads the workflow directive. No filler or restatement of the title.

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 must characterize the return, and it does so by naming the attribute dimensions and in-stock counts plus the filter format to reuse downstream. Minor gaps remain around overall response structure and any pagination, so not a full 5.

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 brand and category slugs are fully documented in the schema (including source tools and patterns). The description adds the return-shape convention {attribute: [value, ...]} but no new parameter-level detail, matching the baseline 3 for schema-dominant definitions.

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 (List) and resource (attribute filters of a category or brand), and enumerates the concrete attribute kinds returned (volume, hair/skin type, gender, origin) plus the in-stock counts. This lets an agent distinguish it from ab_categories/ab_brands (which list the taxonomies themselves) and from ab_browse (which consumes the filters).

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 positions the tool relative to a sibling: 'Use before ab_browse for a size or type,' and even shows the pass-through form {attribute: [value, ...]}. It does not clarify when to supply brand versus category, nor any exclusions, so it stops short of full when/when-not coverage.

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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