detalhar_candidatoFull evaluation of one candidate: score per competency, the evidence behind each score, red flags, highlights and the human decision if there is one. Read-only. Does NOT return phone, e-mail or résumé.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Optional. Language for the text in this tool's response (labels, notes, messages). Defaults to the account's language. | |
| candidateId | Yes | Candidate id, from listar_candidatos. |
Changes observed during successful MCP inspections.
Input schema / properties / candidateIdAdded value: +{
+ "description": "Candidate id, from listar_candidatos.",
+ "type": "string"
+}Input schema / properties / candidato_idRemoved value: -{
- "description": "id do candidato, obtido em listar_candidatos",
- "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 / requiredPrevious value: -[
- "candidato_id"
-]New value: +[
+ "candidateId"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint=true already supplied by annotations, the description adds useful context beyond annotations by stating that it does NOT return phone, e-mail or résumé. It also discloses the return payload composition (scores per competency, evidence, red flags, highlights, human decision), which is valuable because no output schema exists.
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 two compact sentences. It front-loads the core purpose and then immediately adds return details and exclusions, with no wasted words.
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?
Because there is no output schema, the description carries the burden of explaining return values, and it does so by listing the main evaluation components and explicitly noting excluded sensitive fields. For a read-only single-candidate detail tool with full schema parameter coverage, this is complete enough.
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 already documented in the schema. The description does not add syntax, constraints, or default behavior beyond what the schema provides, making the baseline of 3 appropriate.
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 gives a specific verb and resource: 'Full evaluation of one candidate,' and enumerates the returned content (scores, evidence, red flags, highlights, human decision). It is clear on its own, but it does not explicitly differentiate itself from siblings such as entrevistar_candidato or listar_candidatos, so it falls short of the top tier.
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 explains what the tool returns but offers no guidance on when to use it versus alternatives. It does not mention entrevistar_candidato, listar_candidatos, or any other sibling, nor does it state when this evaluation is appropriate instead of another tool.
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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