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Careeronestop Salary

careeronestop_salary
Read-onlyIdempotent

What does pay in — wage percentiles (10th/25th/median/75th/90th, hourly + annual) for a U.S. occupation from the Dept. of Labor CareerOneStop API. Accepts an O*NET/SOC title or code. Example: careeronestop_salary({ occupation: "Registered Nurses", location: "TX", _apiKey: "userId:token" })

Input Schema

NameRequiredDescriptionDefault
_apiKeyYesCareerOneStop credentials as "userId:token" (free at https://www.careeronestop.org/Developers/WebAPI/registration.aspx)
locationYesLocation: state ("TX"), "City, State" ("Reston, VA"), ZIP ("20191"), or "US" for national data
occupationYesOccupation keyword, O*NET/SOC title, or code, e.g. "Registered Nurses" or "29-1141.00"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuine behavioral value beyond that: it describes the shape of the result (five percentiles, hourly and annual figures) and supplies a concrete invocation example. It stops short of pagination/rate-limit/error 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?

Front-loaded with the core question the tool answers, then folds in outputs, source, input type, and an example in a compact block. The single dense sentence plus example is slightly information-packed but nothing is wasted.

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 usefully fills in the return shape and data provider, and the input examples cover both identifier styles and location formats. Complete enough to invoke correctly, though it offers no guidance on choosing this versus the salary-comparison sibling.

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%, so the baseline is 3. The description only restates that occupation accepts an O*NET/SOC title or code and shows a location example, adding no format or normalization detail beyond what the schema already documents.

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 resource (wage percentiles for a U.S. occupation/location), the exact statistics returned (10th/25th/median/75th/90th, hourly + annual), and the data source (Dept. of Labor CareerOneStop). It does not name or distinguish itself against the sibling careeronestop_compare_salary, 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 Guidelines3/5

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

Usage is implied through the worked example and the note that it accepts an O*NET/SOC title or code, which tells the agent what inputs are valid. There is no explicit when-to-use guidance or routing to careeronestop_compare_salary for multi-occupation comparisons.

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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