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irantalent-mcp

irantalent-mcp

by sepehr071

Find companies

it_companies
Read-onlyIdempotent

Search or list companies in IranTalent’s employer directory to find a company ID by name, with ratings, review counts, and open job counts.

Instructions

List or search companies in IranTalent's employer directory (about 34,000), most open jobs first.

Use to find a company id from a name. Each row has rating (1-5, null without reviews), review count and open job count. Next: it_company for the profile, it_search_jobs(company=id) for its jobs, it_company_reviews.

Input Schema

NameRequiredDescriptionDefault
pageNoPage number, 1-based. 30 results per page.
searchNoCompany name (English or Persian), e.g. digikala, نستله.

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 read-only, idempotent, open-world and non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: result ordering, approximate corpus size, and the shape of each row including the null-rating-without-reviews caveat, which matters because there is no output schema. It omits pagination behavior and the 500-page cap, so not quite 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 short blocks: purpose and ordering first, then use case plus next-step routing. The telegraphic "Next:" line is dense but every clause carries actionable information, and there is 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?

For a two-parameter read tool with full annotations and no output schema, the definition supplies everything needed: what it returns row-by-row, how results are ordered, when to choose it, and which tools to call next. Nothing an agent needs in order to invoke it correctly 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 description coverage is 100%, with both page (1-based, 30 per page) and search (English or Persian, with examples) fully documented. The description adds no additional meaning about how search matching works, so this sits at the baseline where the schema does the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("List or search companies in IranTalent's employer directory"), plus scale (~34,000) and default ordering (most open jobs first). It also pins down the actual use case ("find a company id from a name"), which separates it from the profile-level sibling it_company. It never explicitly addresses it_top_companies, the closest overlapping sibling, so it falls short of a 5.

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 when-to-use ("Use to find a company id from a name") and then routes the agent onward with named alternatives: it_company for the profile, it_search_jobs(company=id) for jobs, it_company_reviews for reviews. The exact argument form for the jobs handoff is even shown, leaving nothing to inference.

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