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Job Profile Autocomplete

autocomplete_job_profile
Read-onlyIdempotent

Accepts a partial job title string and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to taxonomy profiles from the moment a recruiter starts typing.

Input Schema

NameRequiredDescriptionDefault
localeNoLocale code.
keywordNoPartial job-title text / prefix to autocomplete (all-lowercase param name 'keyword'), e.g. 'soft', 'data sci'.
languageNoLanguage code.
customvaluesNoCustom taxonomy values.

Output Schema

NameRequiredDescriptionDefault
dataYesTool-specific result payload. The exact fields depend on which tool produced this result.
metaYesRequest metadata: unique trace ID and server-side processing latency.
successNoAlways ``true`` for a successful result. Check this field first to distinguish success from error envelopes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / userkey
      Removed value: -{
      -  "default": "",
      -  "description": "RChilli userkey. Leave blank to use the authenticated session key.",
      -  "title": "Userkey",
      -  "type": "string"
      -}
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive behavior, so the safety profile is fully covered. The description adds that results are ranked and canonicalized, which is useful, but it says nothing about result limits, ranking logic, or behavior on empty/no-match input.

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?

Two sentences with the core behavior front-loaded and no wasted clauses. The second sentence is slightly promotional ('from the moment a recruiter starts typing'), but it still conveys the intended usage context.

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 an output schema present, full parameter documentation, and rich safety annotations, the description only needs to frame purpose and return kind, which it does. Minor gaps around result count and no-match behavior are acceptable for a simple read-only autocomplete endpoint.

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 the keyword parameter is documented with concrete examples ('soft', 'data sci'), so the schema does the heavy lifting. The description only echoes the 'partial job title string' notion and adds nothing about locale, language, or customvalues.

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 verb and resource: accepts a partial job title and returns ranked autocomplete suggestions with canonical titles and job families. The job-title domain implicitly separates it from autocomplete_skill and lookup_job_profile, but no sibling is named explicitly, 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?

The phrase 'from the moment a recruiter starts typing' implies an interactive typeahead use case, but there is no explicit when-to-use or when-to-prefer alternative guidance (e.g., versus lookup_job_profile for exact lookups or autocomplete_skill for skills).

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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