Enter a partial job title to receive matching professional role suggestions. Find the correct role name for your search.
Autocomplete job titles / professional roles. Returns matching role suggestions for partial input.
| Name | Required | Description | Default |
|---|---|---|---|
| raw | No | Return the full raw hh.ru JSON instead of the compact id — name listing. | |
| text | Yes | Partial job title to autocomplete |
Changes observed during successful MCP inspections.
v2.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral details. It only states the basic function ('Returns matching role suggestions') without mentioning side effects, safety, rate limits, or authentication requirements. For a tool with zero annotation coverage, this is a significant gap—agents cannot infer whether this operation is safe or requires special permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every word adds value, with no unnecessary elaboration or repetition. It is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple autocomplete tool with full schema coverage and no output schema, the description is largely sufficient. It covers the primary use case and relies on schema for parameters. Minor omissions (e.g., authentication requirements) exist, but they are not critical for a read-only suggestion tool. The overall completeness is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning both parameters (text and raw) are already documented in the schema. The description adds no extra meaning beyond what the schema provides. Per the rubric, the baseline is 3 when schema covers all parameters, and the description does not compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Autocomplete') and a specific resource ('job titles / professional roles'), which clearly differentiates it from sibling tools like suggest_companies and suggest_areas. It also implies the use case of partial input, making the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for partial input' provides clear context for when to use the tool, but it does not explicitly mention alternatives or when not to use it. Given the sibling tools (e.g., get_professional_roles for full lists), the description lacks explicit exclusions but still gives sufficient guidance for a straightforward autocomplete scenario.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.