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Quera courses

qr_courses
Read-onlyIdempotent

Find Quera College programming courses by level, track, or keyword, with prices and upcoming listings to answer which course teaches a specific topic.

Instructions

List Quera College's paid programming courses (about 70) with level and price.

Use for 'which Quera course teaches X'. price_toman is the list price in Toman; your_price_toman is what a visitor pays now (0 = currently free). Upcoming courses (announced, not yet open) are listed separately. For intensive bootcamps call qr_bootcamps.

Input Schema

NameRequiredDescriptionDefault
levelNoCourse level: beginner (مقدماتی), advanced (پیشرفته), expert (تخصصی, job-ready).
orderNoSort order.
trackNoLearning path slug: python-django, front-end, artificial-intelligence, machinelearning, devops, data-analysis, deep-learning, php-laravel, olympiad, general.
searchNoWords in the course name, e.g. 'پایتون', 'react'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.3/5.0
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 genuinely useful non-annotation context: the two price fields' meaning (list price vs current price, 0 = free) and the fact that upcoming courses are returned separately. It stops short of describing ordering/pagination of results.

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-loaded with the resource and scope in the first sentence, then price semantics, then the sibling routing line. Roughly 60 words with no filler, though the price sentence is slightly dense in phrasing.

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 usefully names the returned fields (level, price) and warns that upcoming courses are listed apart, which an agent needs to parse results. For a four-optional-param read-only listing tool this is close to complete, though result ordering/shape could be clearer.

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 all four parameters (level, order, track, search) are already documented with enums and examples. The description adds no further filtering semantics; its price notes describe return values rather than inputs. Baseline 3 applies.

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 and resource ("List Quera College's paid programming courses"), scopes it with a count (~70) and returned attributes (level, price), and explicitly names the sibling it is not (qr_bootcamps). An agent can distinguish it from the other qr_* listing tools without opening the schema.

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 use case ("Use for 'which Quera course teaches X'") and an explicit routing rule to an alternative ("For intensive bootcamps call qr_bootcamps"). The remaining siblings (jobs, blog, problems) are different domains and need no exclusion.

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