nutshell/examples/02-data-analysis/nutshell.json at main · ChatChatTech/nutshell · GitHub

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{
  "nutshell_version": "0.2.0",
  "bundle_type": "request",
  "id": "nut-2a4b6c8d-e0f1-2345-6789-abcdef012345",
  "created_at": "2026-03-14T14:00:00Z",
  "expires_at": "2026-03-16T14:00:00Z",

  "task": {
    "title": "Analyze User Churn Patterns from Event Logs",
    "summary": "Process 30 days of user event logs to identify churn signals, build a cohort retention matrix, and generate a report with actionable insights. Output as a Jupyter notebook with visualizations.",
    "priority": "medium",
    "estimated_effort": "4h"
  },

  "tags": {
    "skills_required": ["python", "pandas", "data-analysis", "visualization"],
    "domains": ["analytics", "product-metrics"],
    "data_sources": ["s3://analytics-bucket/events/"],
    "custom": {
      "output_format": "jupyter-notebook",
      "data_size": "~2GB",
      "complexity": "medium"
    }
  },

  "publisher": {
    "name": "Analytics Lead",
    "contact": "analytics@example.com",
    "tool": "cursor"
  },

  "context": {
    "requirements": "context/requirements.md",
    "additional": ["context/data-dictionary.md"]
  },

  "files": {
    "total_count": 3,
    "total_size_bytes": 4200,
    "tree": [
      {"path": "files/data/sample_events.csv", "size": 2800, "role": "sample"},
      {"path": "files/src/template.ipynb", "size": 1000, "role": "scaffold"},
      {"path": "files/assets/retention-example.png", "size": 400, "role": "reference"}
    ]
  },

  "apis": {
    "endpoints_spec": "apis/endpoints.json",
    "base_urls": {
      "data_warehouse": "https://dw.internal.example.com"
    },
    "auth_method": "api_key",
    "credential_ref": "credentials/vault.enc.json"
  },

  "credentials": {
    "vault": "credentials/vault.enc.json",
    "encryption": "age",
    "scopes": [
      {
        "name": "s3-readonly",
        "type": "aws_s3",
        "access_level": "read",
        "expires_at": "2026-03-16T14:00:00Z"
      },
      {
        "name": "dw-query",
        "type": "api_key",
        "access_level": "read",
        "rate_limit": "10/min",
        "expires_at": "2026-03-16T14:00:00Z"
      }
    ]
  },

  "acceptance": {
    "criteria_file": "tests/criteria.json",
    "auto_verifiable": false,
    "human_review_required": true,
    "checklist": [
      "Notebook executes end-to-end without errors",
      "Cohort retention matrix covers 30-day window",
      "At least 3 churn signals identified with supporting data",
      "Visualizations are clear and properly labeled",
      "Executive summary section with actionable recommendations"
    ]
  },

  "harness": {
    "agent_type_hint": "execution",
    "context_budget_hint": 0.30,
    "execution_strategy": "one-shot",
    "checkpoints": false,
    "constraints": [
      "Use only pandas, matplotlib, seaborn — no heavy ML libraries",
      "All data processing must handle missing values gracefully",
      "Do not download more than 100MB of raw data for analysis"
    ]
  },

  "resources": {
    "docs": [
      {"url": "https://wiki.example.com/event-schema", "title": "Event Schema Documentation"},
      {"url": "https://wiki.example.com/churn-definition", "title": "Official Churn Definition"}
    ],
    "images": [
      {"path": "files/assets/retention-example.png", "description": "Example retention matrix format"}
    ]
  },

  "compression": {
    "algorithm": "zstd",
    "original_size_bytes": 12000,
    "compressed_size_bytes": 4200,
    "context_tokens_estimate": 2800
  },

  "completeness": {
    "status": "ready"
  },

  "extensions": {
    "clawnet": {
      "peer_id": "12D3KooWAbCdEfGhIjKlMnOpQrStUvWxYz0123456789abcdef",
      "reward": {"amount": 30.0, "currency": "energy"},
      "gossip_topic": "/clawnet/tasks/1.0.0",
      "reputation": 72.0
    }
  }
}