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Search (alias of search_jobs, in ChatGPT's research shape)

search
Read-onlyIdempotent

An ALIAS of search_jobs in the fixed shape ChatGPT's deep-research and company-knowledge connectors call: one query string in, {results:[{id,title,url}]} out. Every result's id is the job id fetch and every other tool take; url is the employer's own apply page when the board holds one, else the posting's page on the site. Same board, same ranking, same limit as an unkeyed search_jobs (10 rows); the disclosures ride beside the results. Any other client should call search_jobs, which takes every filter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFree text — title, skills, a place, exclusions with a leading minus.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
totalNoExact match count. ABSENT with countUnavailable:true when the board refuses to guess.
hasMoreNo
resultsYes
didYouMeanNo
nextOffsetNoPass back as `offset` for the next page.
excludedTermsNo
intentFiltersNoWords read out of the query as filters.
ignoredFiltersNoFilters the board could NOT apply. Results answer a wider question than was asked.
agenciesExcludedNoRow-selecting: disclosed agency inventory is hidden from this page.
countUnavailableNoThe board could not count this query exactly — do not report a total.
salaryStatedOnlyNoRow-selecting: this page excludes the ~76% of postings with no annualised figure in approximate US dollars (2026-09-27), including postings that publish an hourly rate.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / properties / salaryStatedOnly / description
      Previous value: -"Row-selecting: this page excludes the ~87% of postings with no stated pay."New value: +"Row-selecting: this page excludes the ~76% of postings with no annualised figure in approximate US dollars (2026-09-27), including postings that publish an hourly rate."
  2. First observed

TDQS

A4.4/5.0
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 genuinely non-structured context: identical ranking and 10-row limit versus unkeyed search_jobs, that disclosures 'ride beside the results', and that url falls back to the posting's page when no employer apply page exists.

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 alias identity and the shape before the routing advice; every sentence carries distinct information. It is slightly dense across three sentences, but nothing is redundant or 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?

An output schema exists, yet the description still notes the envelope and the id/url meaning that drive cross-tool routing. Combined with the annotations, the only required parameter, and the sibling alternatives, an agent has everything needed to select and call it correctly.

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?

The single query parameter is already 100% documented in the schema, including free-text syntax and leading-minus exclusions. The description only frames it as 'one query string in', adding no syntax or constraint beyond the schema, so the baseline 3 applies.

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 exactly what it is (an alias of search_jobs), the fixed input/output shape, and the response envelope {results:[{id,title,url}]}. It also distinguishes the id's downstream use (fetch and every other tool) and the url's semantics, so an agent can place it precisely against siblings without opening a schema.

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?

Explicitly says which clients should use it (ChatGPT deep-research and company-knowledge connectors) and names the alternative for everyone else: 'Any other client should call search_jobs, which takes every filter.' It also states the equivalence: same board, same ranking, same unkeyed limit of 10 rows.

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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