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Get candidate report

get_candidate_report
Read-only

Get the content of a candidate's scorecard report: ranking, experience, strengths, considerations, criteria verdicts, skills, gaps and suggested interview focus areas. Semata renders the PDF in the browser, so this returns the report as data plus appUrl, the page where the user can download the PDF. Raw CV text is not returned.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspaceId": "<workspaceId>",
      "candidateId": "<candidateId>"
    },
    "name": "get_candidate_report"
  }
}

Input Schema

NameRequiredDescriptionDefault
candidateIdYesThe candidate id, from list_candidates.
workspaceIdYesThe workspace id returned by list_workspaces. Use 'personal' for the personal workspace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds real value beyond that: the PDF is rendered client-side by Semata, so the response is structured data plus appUrl pointing to the download page, and CV text is deliberately excluded. What is missing is any note on error behavior or whether reports may be stale/missing for un-scored candidates.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly packed sentences, front-loaded with purpose and followed by the return-shape clarification. The exclusion note is short and material; no filler.

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 no output schema, the description usefully explains the return shape (report data plus appUrl) and the CV-text omission, which an agent needs to answer follow-up questions. Minor gaps remain around failure modes for candidates without a completed report.

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%; both candidateId and workspaceId are documented with sourcing tools (list_candidates, list_workspaces) and the 'personal' option. The description adds nothing about parameters, so the baseline of 3 applies.

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 ('get the content of a candidate's scorecard report') and enumerates exactly which sections are included (ranking, experience, strengths, criteria verdicts, skills, gaps). It is distinguishable from generic candidates tools by the content list, though it never explicitly names sibling tools like get_candidate or get_screening_report.

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?

Usage is only implied: to see the full report payload rather than CV text, call this tool. The note that 'Raw CV text is not returned' implicitly points to get_candidate for raw data, but no explicit when-to-use or when-not-to-use guidance against siblings is given.

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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