code_review_depth_optimizer

Active

declared in 0.2.0

As a CTO, this tool analyzes your team's historical DORA metrics (deployment frequency, lead time, MTTR, change failure rate) and GitHub pull request data to recommend an optimal code review depth. Input your repository identifier and time range, and receive a structured recommendation on review rigor (light, standard, thorough) with supporting metrics and risk-adjusted rationale.

Parameters schema

{
  "type": "object",
  "required": [
    "repository",
    "timeRangeDays"
  ],
  "properties": {
    "async": {
      "type": "boolean",
      "description": "If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts."
    },
    "teamSize": {
      "type": "number",
      "minimum": 1,
      "description": "Number of active developers in the team"
    },
    "repository": {
      "type": "string",
      "description": "GitHub repository identifier in format owner/repo"
    },
    "riskTolerance": {
      "enum": [
        "low",
        "medium",
        "high"
      ],
      "type": "string",
      "description": "Organization's risk tolerance level"
    },
    "timeRangeDays": {
      "type": "number",
      "maximum": 365,
      "minimum": 7,
      "description": "Number of days of historical data to analyze"
    }
  }
}

What this tool wraps· 0 endpoints

min confidence0.70 0.50

No endpoints wrapped at confidence ≥ 0.70.

Parent server

gapup-mcp

https://github.com/getgapup/gapup-mcp-public

2/7 registries

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