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faradars-mcp
by sepehr071

Course details

fr_course
Read-onlyIdempotent

Fetch details for one Faradars course by slug or URL, including price, discount, duration, rating, instructors, syllabus, prerequisites, and extras; set lessons=true to list every lesson.

Instructions

Get one Faradars course: price and current discount, duration, rating, students, instructors, syllabus.

slug comes from fr_search_courses (a full course URL also works). The syllabus is a list of sections with lesson counts and minutes; set lessons=true for every lesson title. Next: fr_course_reviews for student comments, fr_related_courses for alternatives and follow-ups, fr_compare_courses to weigh several, fr_instructor for the teacher. prerequisites are courses to take first; extras counts the included transcripts, notes and summaries. Prices are Toman.

Input Schema

NameRequiredDescriptionDefault
slugYesSlug or full faradars.org URL, e.g. python-programming-basic-fvpht0064.
lessonsNoAlso list every lesson name with length and free-preview flag (long for big courses).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive, and open-world behavior, so the safety profile is covered. The description adds substantial context beyond annotations: what fields are returned, syllabus structure, the effect of `lessons=true`, what `extras` counts, and that prices are in Toman; only failure modes and pagination are 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?

Front-loads the core operation and then packs routing, input provenance, output details, and sibling alternatives into dense, purposeful sentences. There is little or no filler.

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 carries the burden well: it describes the returned fields, syllabus shape, lesson-list behavior, currency, and which sibling tools to use next. An agent has enough information to call it correctly.

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. The description adds useful provenance for `slug` and clarifies that `lessons=true` lists every lesson title, plus explains related output fields like `prerequisites` and `extras`.

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: 'Get one Faradars course,' then enumerates the returned fields including price, discount, duration, rating, students, instructors, and syllabus. It explicitly distinguishes itself from siblings by directing review, related-course, comparison, and instructor queries elsewhere.

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 clear provenance for `slug` from `fr_search_courses` and notes that a full course URL also works. It names the alternative tools for student comments, alternatives/follow-ups, comparisons, and teacher details, and explains that `prerequisites` are courses to take first.

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