cdp-lite-adapter

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Adapt the User Explorer (CDP-lite) prototype to new data sources by mapping input exports to the build pipeline, updating adapters/enrichments, and preserving output JSON schemas for the UI. Use when asked to connect real data, replace inputs, or modify the build outputs/UI contracts.

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[Data Cleaning]

When & Why to Use This Skill

This Claude skill automates the integration and normalization of new data sources into the CDP-lite User Explorer prototype. It streamlines the process of mapping raw input exports to the build pipeline, updating JavaScript adapters for activity and profile data, and ensuring that output JSON schemas remain consistent with UI contracts, facilitating a seamless transition from prototype to real-world data.

Use Cases

  • Scenario 1: Transitioning from mock data to real customer activity logs by mapping external CSV or JSON exports to the internal build pipeline.
  • Scenario 2: Normalizing disparate user profile fields (e.g., mapping 'Full Name' to 'name' and 'Job Title' to 'title') to ensure UI consistency and data integrity.
  • Scenario 3: Modifying data enrichment rules, such as scoring or segmentation, while preserving the underlying JSON schema to prevent UI breakage during updates.
namecdp-lite-adapter
descriptionAdapt the User Explorer (CDP-lite) prototype to new data sources by mapping input exports to the build pipeline, updating adapters/enrichments, and preserving output JSON schemas for the UI. Use when asked to connect real data, replace inputs, or modify the build outputs/UI contracts.

CDP-lite Adapter

Overview

Map new data sources into the existing CDP-lite build pipeline while keeping output schemas stable for the UI.

Workflow

  1. Identify input formats and field names for activity + profiles.
  2. Update adapters to normalize into the expected fields.
  3. Adjust enrichments (score/segments) only if business rules change.
  4. Run make build and validate data/ outputs against the UI contract.

Adapter Targets

  • scripts/adapters/activity.js
    • Normalize to: email, date, login, total_views, unique_views, dashboard_name (optional)
  • scripts/adapters/profiles.js
    • Normalize to: email, name, department, geo, title, manager_email, skip_level_email

Output Contract

Preserve the output schemas in:

  • data/users/u_<sha1>.json
  • data/index.json
  • data/facets.json
  • data/dashboards.json

For field-level details, read references/data-contract.md.

Notes

  • Weekly activity must include every week from 2025-06-01 to today, Monday week start.
  • Email is the primary key; always normalize to lowercase + trim.
  • Keep activity_score_bucket in the index for filtering.