data-context-extractor-for-table-documentation
Sub-skill of data-context-extractor: For Table Documentation (+2).
Best use case
data-context-extractor-for-table-documentation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of data-context-extractor: For Table Documentation (+2).
Teams using data-context-extractor-for-table-documentation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/for-table-documentation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How data-context-extractor-for-table-documentation Compares
| Feature / Agent | data-context-extractor-for-table-documentation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of data-context-extractor: For Table Documentation (+2).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# For Table Documentation (+2) ## For Table Documentation - **Location**: Full table path - **Description**: What this table contains, when to use it - **Primary Key**: How to uniquely identify rows - **Update Frequency**: How often data refreshes - **Key Columns**: Table with column name, type, description, notes - **Relationships**: How this table joins to others - **Sample Queries**: 2-3 common query patterns ## For Metrics Documentation - **Metric Name**: Human-readable name - **Definition**: Plain English explanation - **Formula**: Exact calculation with column references - **Source Table(s)**: Where the data comes from - **Caveats**: Edge cases, exclusions, gotchas ## For Entity Documentation - **Entity Name**: What it's called - **Definition**: What it represents in the business - **Primary Table**: Where to find this entity - **ID Field(s)**: How to identify it - **Relationships**: How it relates to other entities - **Common Filters**: Standard exclusions (internal, test, etc.) ---
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