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moonie0201

ats-jobs-mcp

by moonie0201

resolve_company

Map a company name or career-site URL to the provider:slug pair used by search_jobs. Reads URLs directly, matches names against the CC-BY ats-directory, and returns status for each match.

Instructions

Map a company name or career-site URL to the 'provider:slug' pair that search_jobs takes, using the public CC-BY ats-directory. A URL is read directly; a name is matched against the directory. Returns every match, with 'status' saying whether that board answered when last probed (ok / dead / unconfirmed). Free — no Apify run, no billing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
url_or_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well: it names the data source (public CC-BY ats-directory), explains that URLs are read directly while names are matched, notes that every match is returned, defines status values, and clarifies there is no Apify run or billing. Minor gaps like no-match behavior are not covered, but the key behavioral traits are disclosed.

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?

The description is four sentences, each earning its place: purpose, input-type handling, output/status semantics, and cost. It is front-loaded with the core purpose and contains 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?

Given a single parameter, an output schema that can document return structure, and no annotations, the description provides sufficient context: what the tool does, how the input is interpreted, what matches include, and that it is free. Nothing essential for selecting or invoking the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema only defines 'url_or_name' as a string with 0% schema description coverage, so the description must compensate. It does so thoroughly by specifying both accepted forms (company name or career-site URL) and how each is processed. This adds real meaning beyond the bare schema.

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 uses a specific verb ('Map') and a resource ('company name or career-site URL') to produce a clearly defined output ('provider:slug' pair). It also explicitly ties this to search_jobs, making the tool's role distinct from its siblings without needing to open schemas.

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

Usage Guidelines4/5

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

The description clearly implies when to use this tool: before calling search_jobs, since it produces the pair search_jobs consumes. It also clarifies behavior for the two supported input types (URL vs. name). It does not explicitly state exclusions or compare against list_supported_ats, but the context is clear enough.

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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