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bi-python-knowledge

Guides governed single-node source preparation, cleaning, grain, and aggregation reasoning in Python.

2|Updated Jun 22, 2026
Search Tags:#python#aggregation#data cleaning#power bi#source preparation#grain definition#retail data
One-click install
npx skills add https://github.com/Kemetra/Seshat-BI --skill bi-python-knowledge-kemetra
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bi-python-knowledge
Source: https://github.com/Kemetra/Seshat-BI/tree/main/distribution/bundle-templates/shared/skills/bi-python-knowledge
Command: npx skills add https://github.com/Kemetra/Seshat-BI --skill bi-python-knowledge-kemetra

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Retail data preparation often happens without governance, leading to unsafe cleaning choices, wrong grain decisions, and unverifiable aggregations. This Skill routes you to Seshat's curated Python knowledge so source preparation follows explicit stop rules and human decision gates. ## Core Features & Use Cases - Routed Knowledge Access: Opens the bi-python-knowledge INDEX and selects only the route relevant to your current task instead of loading everything. - Governed Preparation Guidance: Covers single-node source preparation, cleaning, grain definition, and aggregation reasoning with explicit stop rules. - Safety Boundary Enforcement: Blocks execution against live data unless the user explicitly requests it in scope and provides the required connection boundary. - Use Case: While profiling a messy retail CSV before warehouse loading, ask for cleaning and grain guidance, and the Skill pulls only the relevant knowledge route with its decision checkpoints. ## Quick Start Ask the assistant to use the bi-python-knowledge skill to guide cleaning and grain decisions for your retail source file.

Frequently Asked Questions about bi-python-knowledge

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

FAQPage Schema
How do I prepare retail source data for a BI warehouse in Python?▼

Use this Skill to open the bi-python-knowledge INDEX and select the route matching your task, such as cleaning or grain definition. It provides governed guidance with stop rules rather than executing transformations directly against your data.

What is grain definition in data preparation?▼

Grain definition specifies the level of detail each row in a dataset represents, such as one row per transaction or per day per store. The Skill's knowledge routes cover grain reasoning as a human decision gate before aggregation.

Does this Skill execute Python code against my live data?▼

No, it does not execute against live data by default. Execution requires your explicit in-scope request and a defined connection boundary, as stated in the Skill's operating instructions.

When should I use aggregation reasoning before Power BI?▼

Use it during source preparation, before loading the medallion warehouse, to ensure rollups match the defined grain and business rules. This prevents dashboards from showing unreconciled or undefined metrics later.

What are the limitations of this knowledge-routing Skill?▼

It is limited to single-node source preparation scenarios and only provides guidance from the indexed knowledge routes. It does not perform distributed processing, automated remediation, or direct warehouse operations.

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