ikf-forecast-ingest-validator

Name: ikf-forecast-ingest-validator
Availability: InStock
Author: HeyFlou

Validate CSV and XLS forecast files into canonical database rows.

Updated Aug 23, 2026

Search Tags:#validation #data pipeline #etl #csv #forecast #ingest #heatmap

Ready to run

npx skills add https://github.com/heyflouai/ikf-central-dashboard --skill ikf-forecast-ingest-validator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ikf-forecast-ingest-validator
Source: https://github.com/heyflouai/ikf-central-dashboard/tree/main/.claude/skills/ikf-forecast-ingest-validator
Command: npx skills add https://github.com/heyflouai/ikf-central-dashboard --skill ikf-forecast-ingest-validator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill ensures that forecast data, whether in column-based or heatmap formats, is correctly parsed, validated, and mapped into a canonical database structure, guaranteeing accurate representation in UI surfaces.

Core Features & Use Cases

Multi-Format Ingest: Supports both CSV (column-based) and XLS (heatmap-based) forecast files.
Data Validation: Enforces strict rules for tickers, horizons, signal, and predictability values.
Canonical Mapping: Ensures data conforms to a defined database schema for consistent rendering.
Use Case: Uploading daily stock market forecast data in CSV format to ensure all tickers are correctly identified, horizons are mapped (e.g., '3d' to '3D'), and signal/predictability values are within acceptable ranges before they are displayed on a financial dashboard.

Quick Start

Use the ikf-forecast-ingest-validator skill to validate the attached CSV file 's&p500_stocks_flat.csv' for ingest.

Frequently Asked Questions about ikf-forecast-ingest-validator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I validate forecast data ingest before loading it into a database?▼

Forecast data ingest validation parses column-based CSV and heatmap-based XLS files, enforcing strict rules for tickers, horizons, and predictability values to ensure accurate mapping into canonical database rows for UI rendering.

How do I parse and map a heatmap-based forecast file?▼

Parsing a heatmap-based forecast file involves extracting real number signals and 0.xx predictability values, then mapping them into a Heatmap Contract output and canonical database rows for accurate dashboard rendering.

Can I validate both CSV and XLS forecast files for data pipeline ingest?▼

Yes, multi-format ingest supports validating both column-based CSV and heatmap-based XLS forecast files, ensuring all tickers, horizons, and real number signals conform to strict database schema rules.

What rules apply to predictability and signal values during forecast data validation?▼

During forecast data validation, strict rules enforce that signal values are real numbers and predictability values follow a 0.xx format, ensuring correct horizon mapping before data enters the canonical database structure.

Why does my forecast horizon mapping fail during ETL ingest?▼

Forecast horizon mapping fails during ETL ingest when horizon formats are not correctly normalized, such as failing to map '3d' to '3D', preventing accurate rendering in canonical database rows.

Do I need to normalize horizon formats before validating stock market forecast data?▼

You do not need to manually normalize horizon formats before validating stock market forecast data, as the validation process automatically maps values like '3d' to '3D' to ensure canonical database schema compliance.