interview-notes
Skill0 starsChanged 42 days agoMITView on GitHub
Turn recorded interviews into structured notes, and compare several of them. Use for customer and user interviews, candidate interviews, research sessions and expert calls, and when the user asks what people said about a topic across conversations.
In this repository3 other files it gives its agents.
- find-the-momentSkill
- lecture-notesSkill
- meeting-followupSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
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 13
Keep the person's words separate from the reading of them.
- Distinctive: line 15
When a transcript is a translation made in RiverScript, say so where you quote it: the wording is the translator's, not the speaker's.
≈ “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
An interview is worth more as structure than as prose, and worth most when it can be compared with the others.
- Find the interview with
list_transcriptswhen the user names it, orsearch_transcriptswhen they describe what was discussed. For a candidate or a customer, their name is usually said out loud and searchable. - Fetch it with
get_transcriptand read it whole. Interviews turn on wording, hesitation and what a person returned to twice, and a search passage loses that. - Produce notes in the shape the user asked for. When they did not ask for a shape, use: what the person wants, what gets in their way today, what they do instead, and quotes worth keeping, verbatim and marked as quotes.
- For a comparison, fetch each interview and answer question by question rather than person by person, so the agreement and disagreement are visible in one place. Name who said what.
Keep the person's words separate from the reading of them. A quote and a conclusion look alike in a summary and matter very differently to the person deciding on it.
When a transcript is a translation made in RiverScript, say so where you quote it: the wording is the translator's, not the speaker's.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

