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data-context

Detect input types, profile data, extract document information, and update analysis_context.md.

Updated Mar 3, 2026
Search Tags:#ssot#data-profiling#document-parsing#data-discovery#analysis-context#japanese-encoding
One-click install
npx skills add https://github.com/mutsumi-yamamoto/claude-data-analysis-marketplace --skill data-context
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-context
Source: https://github.com/mutsumi-yamamoto/claude-data-analysis-marketplace/tree/main/plugins/data-analysis/skills/data-context
Command: npx skills add https://github.com/mutsumi-yamamoto/claude-data-analysis-marketplace --skill data-context

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill centralizes and clarifies project analysis context so teams can start data work with a validated single source of truth, reducing misunderstandings, rework, and silent assumptions.

Core Features & Use Cases

  • Input type detection and routing: Automatically distinguishes between data files (CSV, Excel), business documents (PDF, meeting notes), combined inputs, or no input and selects the appropriate processing path.
  • Quick data profiling and document extraction: Lists files, previews schema and basic statistics, extracts quantitative facts and business-relevant items from documents, and surfaces biases or missing information.
  • SSOT update and execution logging: Reads and updates analysis_context.md with inferred scope, data source metadata, risks, and an execution log entry, then recommends the next analytical step.
  • Use Case: When starting a new analytics engagement, run this Skill to ingest uploaded CSVs and meeting notes, populate the analysis_context.md sections, log the session, and receive the recommended next action.

Quick Start

Use the data-context skill to scan the project data and documents, update analysis_context.md with findings, and append an execution log entry.

Frequently Asked Questions about data-context

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

FAQPage Schema
How do I consolidate project analysis context from mixed CSV, Excel, and PDF inputs?▼

To consolidate analysis context, this Skill detects uploaded file types, profiles data schemas, extracts document facts, and updates an analysis_context.md single source of truth file with the combined findings.

What is the best way to start data discovery and scoping for a new analytics engagement?▼

Data discovery begins by ingesting mixed business documents and data files, automatically previewing schemas, listing basic statistics, and surfacing missing information to validate the initial project scope.

Can I parse Japanese text encodings from meeting notes and data files during initial data profiling?▼

Yes, Japanese text encodings are supported when parsing meeting notes and data files, allowing accurate extraction of business-relevant items and quantitative facts without character corruption.

How do I maintain a single source of truth for stakeholder requirements and data source metadata?▼

Maintain a single source of truth by reading and updating an analysis_context.md file with inferred scope, detected data source metadata, identified risks, and appended execution logs after each session.

Does this approach work with combined data-document submissions or only standalone files?▼

This approach works with combined data-document submissions, automatically routing mixed inputs to the appropriate processing path to extract both data statistics and document context.

What should I do after updating the analysis context and logging the session?▼

After updating the analysis context and appending the execution log, the Skill recommends the next analytical step, guiding you toward deeper analysis based on the validated scope and discovered risks.

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