Fetch raw ad creative, app, ranking, and revenue data from AdMapix as structured JSON.
Design & media
AdMapix Raw Data Developer Helper
Try itDesign and harden AdMapix-style raw data workflows for creative, app, ranking, revenue, and analytics datasets before they become dashboards or agent tools....
What it does
Use this skill when a user needs to ingest, normalize, inspect, or expose raw advertising/app-market data while keeping provenance, schema drift, deduplication, and downstream safety under control.
The skill document
AdMapix Raw Data Developer Helper
Purpose
Use this skill when a user needs to ingest, normalize, inspect, or expose raw advertising/app-market data while keeping provenance, schema drift, deduplication, and downstream safety under control.
Audience: data engineers, growth analysts, skill authors, and agent builders adapting popular AdMapix-style raw data workflows.
Read references/requirement-plan.md when demand evidence, source links, scoring rationale, or review criteria are needed.
Workflow
- Identify raw sources, refresh cadence, entity keys, metrics, dimensions, privacy constraints, and target consumers.
- Create a source-to-table map that separates immutable raw captures from cleaned views, feature extracts, and presentation layers.
- Specify validation rules for required columns, date ranges, currency, locale, creative IDs, app IDs, duplicate rows, and missing metrics.
- Plan failure handling for API quota, partial exports, schema drift, backfill gaps, and vendor naming changes.
- Recommend lightweight local implementation steps using CSV, JSON, SQLite, or DuckDB before heavier warehouse work.
- Return an audit trail with source, transform version, row counts, anomalies, and consumer-facing caveats.
Expected Outputs
- A raw-to-clean data model for AdMapix-style inputs.
- Validation checks for schema drift, duplicates, missing values, and metric consistency.
- A local script or pseudocode plan for ingestion and normalization.
- A reliability checklist for publishing the workflow as an agent skill.
Validation
- Raw data remains reproducible and separate from cleaned outputs.
- Every transform records source, timestamp, row count, and known anomalies.
- The workflow handles partial data, schema drift, and quota failures explicitly.
- The recommended implementation can run on ordinary CPU hardware.
Triggers
Keywords: AdMapix, raw data, app analytics, creative data, rankings, revenue, ETL, data quality
Example trigger sentences:
Use $software-data-admapix-raw-developer-helper to design a raw data layer for ad creative exports.Clean this app-ranking CSV without losing the original source data.Create validation checks for an AdMapix-style analytics skill.
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