data-context-extractor-step-1-load-existing-skill
Sub-skill of data-context-extractor: Step 1: Load Existing Skill (+3).
Best use case
data-context-extractor-step-1-load-existing-skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of data-context-extractor: Step 1: Load Existing Skill (+3).
Teams using data-context-extractor-step-1-load-existing-skill 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/step-1-load-existing-skill/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How data-context-extractor-step-1-load-existing-skill Compares
| Feature / Agent | data-context-extractor-step-1-load-existing-skill | 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: Step 1: Load Existing Skill (+3).
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
# Step 1: Load Existing Skill (+3) ## Step 1: Load Existing Skill Ask user to upload their existing skill (zip or folder), or locate it if already in the session. Read the current SKILL.md and reference files to understand what's already documented. ## Step 2: Identify the Gap Ask: "What domain or topic needs more context? What queries are failing or producing wrong results?" Common gaps: - A new data domain (marketing, finance, product, etc.) - Missing metric definitions - Undocumented table relationships - New terminology ## Step 3: Targeted Discovery For the identified domain: 1. **Explore relevant tables**: Use `~~data warehouse` schema tools to find tables in that domain 2. **Ask domain-specific questions**: - "What tables are used for [domain] analysis?" - "What are the key metrics for [domain]?" - "Any special filters or gotchas for [domain] data?" 3. **Generate new reference file**: Create `references/[domain].md` using the domain template ## Step 4: Update and Repackage 1. Add the new reference file 2. Update SKILL.md's "Knowledge Base Navigation" section to include the new domain 3. Repackage the skill 4. Present the updated skill to user ---
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