Skip to main content
Glama
jmaitlandsoto

ats-scanner-mcp

Extract keywords from a job posting

extract_job_keywords
Read-only

Extract ATS-relevant signals from a job posting: title, company, required/preferred skills with counts, certifications, education, experience, and recurring phrases for resume keyword gap analysis.

Instructions

Pulls the ATS-relevant signals out of a job posting: title, company, hard skills and soft skills (with required/preferred importance and mention counts), education/certification requirements, minimum years of experience, and recurring phrases not in the skills dictionary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_textYesFull text of the job posting.
job_titleNoOverride the detected title.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral detail about what is extracted, including required/preferred importance, mention counts, and handling of phrases not in the skills dictionary. It does not contradict the annotations and provides a clear model of the tool's output behavior.

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?

The description is a single sentence that front-loads the core action and then lists the extracted signals compactly. It is somewhat detailed but every listed element contributes to understanding the output, so it justifies its length.

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 takes on the responsibility of explaining the return content, and it does so by naming the main output dimensions. It could mention the return format or behavior on invalid input, but the core information needed to call the tool is present.

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%, and both parameters are documented with clear descriptions. The tool description adds no parameter-specific semantics beyond the schema, so the baseline of 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?

The description states a specific verb ('Pulls') and a specific resource ('a job posting'), then enumerates the exact categories of output. It is clearly distinct from the resume-oriented sibling tools.

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

Usage Guidelines3/5

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

The description makes the input source explicit and the use case fairly clear, but it does not name any alternatives or state when to choose this tool instead of scan_resume or parse_resume. The usage context is implied rather than explicitly defined.

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