MCP MeasureMCP Measure

index observed

Interviewer Agent by Nova (CIVAI)

I do everything related to interviews and structured Q&A

Should I use this

Quality & Safety

B
Description quality
80%
Schema completeness
90%
Naming quality
67%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Findings (4)

  • LOWTool 'interviewer__voice_interview_questions' description lacks action verbin interviewer__voice_interview_questions
  • LOWTool 'interviewer__converse' description lacks action verbin interviewer__converse
  • LOWTool 'interviewer__voice_interview_questions' name length outside 3-30 rangein interviewer__voice_interview_questions
  • LOWTool 'interviewer__resume_cv_generation' name length outside 3-30 rangein interviewer__resume_cv_generation

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~164Tokens (tool definitions)
~347 BTypical response size
Minimal attention impact (0.13% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "interviewer-agent": {
      "url": "https://nova.civai.co/mcp/agents/interviewer-agent"
    }
  }
}

Remote endpoints

https://nova.civai.co/mcp/agents/interviewer-agentstreamable-http

What it can do

Tool inventory

Tools (3)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
⚪interviewer__voice_interview_questions(detail)

🎤 Interviewer: voice interview questions

Input Schema

{
  "type": "object",
  "properties": {
    "detail": {
      "type": "string",
      "description": "Specific parameters for this action."
    }
  }
}
⚪interviewer__resume_cv_generation(detail)

🎤 Interviewer: resume cv generation

Input Schema

{
  "type": "object",
  "properties": {
    "detail": {
      "type": "string",
      "description": "Specific parameters for this action."
    }
  }
}
⚪interviewer__converse(reply_hint)

Reply conversationally when the request is ambiguous or needs clarification.

Input Schema

{
  "type": "object",
  "properties": {
    "reply_hint": {
      "type": "string",
      "description": "Optional hint for the conversational reply."
    }
  }
}

Community

Rate this Server

Evidence

Recent observations

verifiedversion not recorded3 tools
verifiedversion not recorded3 tools