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sepehr071

technolife-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Suggest products

tl_suggest
Read-onlyIdempotent

Resolve product names to Technolife codes for product, compare, and review lookups. Handles Persian or English queries and returns up to 30 matching codes, not prices.

Instructions

Turn a product name into Technolife product codes (typeahead, up to 30 products, no prices).

Use to resolve a name like 'آیفون 16' to codes for tl_product / tl_compare / tl_reviews. For prices, filters and paging use tl_search.

Input Schema

NameRequiredDescriptionDefault
queryYesProduct name, Persian or English, e.g. 'آیفون 16'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.3.0
    • changedInput schema / properties / query / description
      Previous value: -"Product name or words, Persian or English, e.g. 'آیفون 16' or 'لپ تاپ لنوو'."New value: +"Product name, Persian or English, e.g. 'آیفون 16'."
    • removedInput schema / properties / query / title
      Removed value: -"Query"
    • removedInput schema / title
      Removed value: -"tl_suggestArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "tl_suggestDictOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the description earns credit by adding return-behavior context: typeahead semantics, a cap of up to 30 products, and the explicit absence of prices. It still doesn't say whether results are ranked, fuzzy-matched, or what happens on no match, but the added detail goes meaningfully beyond the annotations.

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 paragraphs, front-loaded with the core transformation and scope, followed by the routing guidance. No sentence is wasted.

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?

With no output schema, the description compensates by describing what comes back (codes, up to 30, no prices) and where those codes are consumed. Nothing essential for correct invocation 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 coverage is 100% with a single 'query' parameter that already documents Persian/English input and the 'آیفون 16' example, so the description's example repeats the schema. Baseline 3 applies since the schema carries the parameter burden.

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+resource transformation: turns a product name into Technolife product codes, and explicitly frames itself as a typeahead. The parenthetical scope ('up to 30 products, no prices') further sharpens what it does versus what it doesn't.

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?

Names both the when-to-use ('resolve a name like آیفون 16 to codes for tl_product / tl_compare / tl_reviews') and the when-not-to-use with the alternative ('For prices, filters and paging use tl_search'). An agent can route between tl_suggest and tl_search without opening either schema.

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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