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sepehr071

torob-mcp

by sepehr071

Price chart

tb_price_chart
Read-onlyIdempotent

Check a product's weekly minimum and average prices in Toman over about a year to decide if now is a good time to buy, with a verdict on the current price level.

Instructions

Price chart of a product (about a year, weekly): minimum and average price in Toman, with a buy-now verdict.

Use to see if now is a good time. summary.verdict is great / fair / high from where today's minimum price sits among the period's weeks (percentile 0 = cheapest of the period). Dates are ISO (converted from Jalali). For notable moves only see tb_price_history; for a full buying decision tb_deal_check.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pointsNoLatest chart points to return (default 26, about 6 months; Torob has about 52 weekly points).
productYesProduct id (the UUID from search cards, e.g. '57ea65ae-0798-4cd0-96a7-38d8af180345'), a '/p/<id>/...' path or a full torob.com product URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), and the description adds real operational context: the ~1-year weekly data window, Toman pricing, ISO dates converted from Jalali, and how the verdict is derived. It stops short of any rate-limit, auth, or pagination guidance, so not a full 5.

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-loads what the tool returns, then interpretation rules, then sibling routing — a sensible order with no filler sentences. The line break inside the verdict paragraph is slightly awkward but costs nothing.

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?

There is no output schema, so the description carries the burden of explaining returns, and it does: min/average price, the great/fair/high verdict values, and the percentile scale where 0 means cheapest. An agent can both call and interpret the result correctly.

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%, so both `points` and `product` are already documented, including the default of 26 and the ~52-point cap. The description's "about a year, weekly" adds only loose framing and doesn't explain what a smaller `points` value does to the verdict window, so the baseline 3 is correct.

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 (product price chart), its scope (~1 year, weekly), and exactly what it returns: minimum and average price in Toman plus a buy-now verdict. It also distinguishes itself from tb_price_history and tb_deal_check by name, so an agent can route without opening schemas.

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?

Gives an explicit selection condition ("Use to see if now is a good time") and names two alternatives with the conditions that select them: tb_price_history for notable moves only, tb_deal_check for a full buying decision. Nothing is left to inference.

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