interview-cleanup
Skill114 starsChanged 10 months agoMITView on GitHub
Clean up raw interview transcripts while preserving meaning and speaker voice. Use after conducting interviews.
In this repository48 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- assumption-mappingSkill
- assumption-prioritizationSkill
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- brainstormingSkill
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- decision-reversibilitySkill
- difficult-conversationsSkill
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- frontend-designSkill
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- jtbd-extractionSkill
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- llm-coding-guardrailsSkill
- mece-analysisSkill
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- tddSkill
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The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
After conducting user interviews when you have raw transcripts that need cleanup before analysis.
- Distinctive: line 31
Don't over-formalize casual language
- Distinctive: line 32
Don't cut unnecessarily
- Distinctive: line 43
Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Interview Transcript Cleanup
Clean up raw interview transcripts while preserving meaning and speaker voice.
When to Use
After conducting user interviews when you have raw transcripts that need cleanup before analysis.
The Process
- Read the full transcript to understand context and flow
- Remove noise without losing meaning:
- Filler words (um, uh, like, you know)
- False starts (incomplete/abandoned sentences)
- Redundancies (repeated words that don't add meaning)
- Preserve what matters:
- Original meaning and intent
- Speaker's unique voice and style
- Speaker labels (Interviewer:, Interviewee:)
- Unclear/inaudible markers [inaudible]
- Light editing only:
- Fix punctuation and capitalization
- Don't over-formalize casual language
- Don't cut unnecessarily
Quality Check
- Does the cleaned transcript read naturally?
- Is the original meaning preserved?
- Can you still hear the speaker's voice?
- Are all speakers clearly labeled?
When Not to Use
Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.
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