Individual skill
qualitative-engine
Activate when the user needs to analyze qualitative data — interview transcripts, field notes, or open-ended survey responses. Handles structured summarization, thematic coding, cross-case analysis, theme matrices, and evidence retrieval. Designed to solve the context-window problem: generates compact summaries first, then works from summaries instead of full transcripts. Only loads full text when specific quotes are needed. Supports Gioia, Mayring, Grounded Theory, and general thematic analysis workflows.
skills/qualitative-engine/SKILL.md
Source commit 160df4d13d266411f0850c4de7ecdbd93e8b40be
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Local scripts
- Last checked
- Nov 11, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 20
- Repository last updated
- Apr 10, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
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- engineering Derived category
- data Derived category
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- productivity-notes Derived category
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> **Orchestration Log**: When this skill is activated, append a log entry to `outputs/orchestration_log.md`:
> ```
> ### Skill Activation: Qualitative Engine
> **Timestamp:** [current date/time]
> **Actor:** AI Agent (qualitative-engine)
> **Input:** [brief description of the analysis request]
> **Output:** [brief description — e.g., "23 interviews summarized, 14 first-order codes identified"]
> ```
# Qualitative Engine
## Core Principle: Summary-First, Full-Text-on-Demand
**CRITICAL:** Qualitative data (interview transcripts) can easily overflow the context window.