Resolve hh.ru skill IDs into readable names. Accepts 1–50 IDs, returns compact id–name listing.
Resolve skill names by id via /skills (1–50 ids). Use suggest_skill_set to discover ids by name first.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Skill id(s) to resolve (1–50). hh.ru /skills requires ids — use suggest_skill_set to find them by name. | |
| raw | No | Return the full raw hh.ru JSON instead of the compact id — name listing. |
Changes observed during successful MCP inspections.
v2.2.1Input schema / properties / idAdded value: +{
+ "anyOf": [
+ {
+ "minLength": 1,
+ "type": "string"
+ },
+ {
+ "items": {
+ "minLength": 1,
+ "type": "string"
+ },
+ "maxItems": 50,
+ "minItems": 1,
+ "type": "array"
+ }
+ ],
+ "description": "Skill id(s) to resolve (1–50). hh.ru /skills requires ids — use suggest_skill_set to find them by name."
+}Input schema / requiredAdded value: +[
+ "id"
+]v2.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure. It mentions the endpoint, the range of ids, and the effect of the raw parameter (full JSON vs compact listing). It does not cover error cases or rate limits, but these are typical for a read operation and not required for basic use. The description gives a solid behavioral overview.
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?
Two sentences with no filler. The primary action and endpoint are front-loaded, and the usage alternative follows naturally. Every word contributes.
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?
The tool is simple with only two parameters and no output schema. The description explains what it returns (skill names) and the raw option, plus the prerequisite for using suggest_skill_set. All necessary information for correct invocation is present.
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%, so the baseline is 3. The description adds value by contextualizing the id parameter (skill ids to resolve) and pointing to suggest_skill_set for name-based discovery, which is not in the schema. The raw parameter is already well-described in the schema, but the description's guidance compensates slightly beyond baseline.
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-resource pair ('Resolve skill names by id') and explicitly names the endpoint /skills. It differentiates itself from suggest_skill_set by clarifying the discovery direction (ids vs names), making it easy to distinguish from sibling tools without inspecting schemas.
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?
Provides explicit guidance: 'Use suggest_skill_set to discover ids by name first.' This tells the agent when to use this tool vs the alternative. Also specifies the id range (1–50), setting a clear precondition for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.