detalhar_vagaShows one job in detail, including the competencies Aya (the AI interviewer) evaluates and the weight of each — the criteria behind every candidate score. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| jobId | Yes | Job id, from listar_vagas. | |
| language | No | Optional. Language for the text in this tool's response (labels, notes, messages). Defaults to the account's language. |
Changes observed during successful MCP inspections.
Input schema / properties / jobIdAdded value: +{
+ "description": "Job id, from listar_vagas.",
+ "type": "string"
+}Input schema / properties / languageAdded value: +{
+ "description": "Optional. Language for the text in this tool's response (labels, notes, messages). Defaults to the account's language.",
+ "enum": [
+ "pt-BR",
+ "pt-PT",
+ "en",
+ "es",
+ "de",
+ "fr"
+ ],
+ "type": "string"
+}Input schema / properties / vaga_idRemoved value: -{
- "description": "id da vaga, obtido em listar_vagas",
- "type": "string"
-}Input schema / requiredPrevious value: -[
- "vaga_id"
-]New value: +[
+ "jobId"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false. The description repeats 'Read-only' without adding behavioral context such as permissions, rate limits, or response format. The note about competencies is about output content, not behavior beyond annotations.
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, front-loaded with the core purpose and a trailing safety confirmation. No wasted words; every sentence 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?
With no output schema, the description usefully indicates what the tool returns (job details, competencies, weights). It omits any mention of how to obtain the jobId, but the schema covers that. Overall complete enough for a simple read tool.
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 both parameters are fully documented in the schema. The description adds no parameter-level meaning beyond what is already in the schema, which is the baseline expectation.
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?
States a specific verb ('Shows') and resource ('one job') with detail on what is included (competencies and weights). It clearly distinguishes from listar_vagas by being singular, but does not explicitly name or contrast with any sibling tool in the description text.
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 description only states what the tool does; it gives no guidance on when to use it versus alternatives like listar_vagas or detalhar_candidato. The schema's jobId description hints at using listar_vagas first, but that is not in the tool description.
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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