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Job Spotter: Check a job link someone pastes

jobspotter_check_job_link
Read-onlyIdempotent

Job Spotter. Check a job link someone pastes. For "is this job real?", "what does this one pay?" with a link. Reads the advert from the employer's job board (Greenhouse, Lever, SmartRecruiters, Ashby and most career pages) and gives the title, company, place, pay, when it was posted, whether it looks like a live, open job, visa sponsorship and a short summary. LinkedIn, Indeed and Glassdoor pages can't be read; the advert text can be pasted into the CV match instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe full link to the job advert.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

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. The description adds valuable behavior beyond annotations: supported sources (Greenhouse, Lever, etc.), unsupported sources, and the exact output fields returned. It doesn't cover rate limits or error handling, but for a read tool this is substantial.

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 the purpose and usage, and the detailed output list and limitation are informative. However, the opening 'Job Spotter. Check a job link someone pastes.' repeats the title and could be trimmed; otherwise efficient.

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?

Given no output schema, the description carries the burden of return values and does so by listing the fields. Annotations cover safety, and the description adds source coverage and limitations. It is complete enough for an agent to invoke correctly, though it omits error scenarios.

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% for the single url parameter, so the schema already documents the parameter. The description adds 'with a link' but no syntax or format details beyond the schema, so baseline 3 is appropriate.

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 ('check') and resource ('job link'), and elaborates that it reads the advert from employer job boards and returns title, company, place, pay, etc. It distinguishes itself from search-oriented siblings by focusing on a pasted link and from CV match for unreadable pages.

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 explicit when-to-use scenarios ('is this job real?', 'what does this one pay?' with a link) and a when-not with alternative: LinkedIn/Indeed/Glassdoor pages can't be read, so paste advert text into CV match instead. This provides clear routing for the main edge case.

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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