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Jobs Naukri Com

jobs_naukri_com
Read-only

Naukri.com (India) job search: job id, title, company, company rating and review count (AmbitionBox), experience range, salary text when shown, locations, description snippet, skill tags, posted label and link, 20 per page (page 1 to 5), plus the total count from the page title. From naukri.com's public search pages through a rendering residential proxy. Price: $0.02 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

NameRequiredDescriptionDefault
qYesKeyword, e.g. 'python', 'data analyst', 'java developer'
pageNoResults page 1 to 5 (default 1)
locationNoOptional city, e.g. bangalore, pune, mumbai

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Beyond the readOnly/openWorld annotations, the description discloses the acquisition path (rendering residential proxy), the billing model ($0.02 USDC per successful call via x402 on three chains) and the crucial fact that failed calls are free, which tells an agent retries are safe. It omits rate limits, latency, and blocking/failure modes that a proxy-scraped source can exhibit.

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?

A single front-loaded sentence puts purpose first, then fields, then operational terms; nothing is padded with marketing language. The long comma-separated field list is dense and partly redundant with the output schema, which slightly weakens its efficiency.

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?

For a paid, proxy-scraped search tool the description covers what an agent needs to call it responsibly: cost, failure charging, pagination cap, and data provenance. With an output schema present, the enumerated return fields are a bonus rather than a necessity, so only minor gaps (rate limits, result freshness) remain.

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% and all three parameters are documented in the schema itself, so the baseline is 3. The description's page-range and page-size note ('20 per page (page 1 to 5)') adds a small amount of context about result volume but nothing beyond what the schema's 'page 1 to 5' already states.

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?

The opening clause names a specific verb and resource ('Naukri.com (India) job search') and the source domain itself differentiates it from the many other job-board siblings. It does not, however, explicitly contrast itself with peers such as jobs_indeed or jobs_foundit_jobs, so sibling differentiation is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no 'use this when' statement, no prerequisites, and no mention of when a competing India or global job board tool would be preferable. The only constraints given are operational (pages 1-5, 20 per page), which govern invocation rather than selection.

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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