Use feedback-synthesis

Turn raw customer feedback

Turn raw customer feedback — interview notes, support tickets, NPS or CSAT verbatims, app-store reviews, sales-call notes — into ranked themes a product decision can rest on, each a problem statement rather than a feature request, counted by distinct people or accounts not mentions, with segments, severity kept separate from frequency, verbatim quotes with source IDs, what people value, where sources disagree, what the sample cannot tell, and the questions for the next interviews. A stdlib script computes the counts.

Reach for it when the user says "what are customers telling us", "synthesise this feedback", "find the themes in these tickets / reviews / NPS comments", "affinity map these interview notes", or "what should we fix first based on feedback".

Install it

npx skilldrop-cli install feedback-synthesis                 # Claude Code, your user folder
npx skilldrop-cli install feedback-synthesis --project       # Claude Code, this repo
npx skilldrop-cli install feedback-synthesis --ide cursor    # or kiro, codex, antigravity, copilot

It is part of the Product manager pack: --pack product-manager installs it with its neighbours.

It ships scripts, so it needs Python 3 (standard library only, nothing to install). What they may touch is declared in its manifest.

Ask for it

Say it the way you would to a colleague. Requests like these route to it:

• "Here are 200 support tickets and last quarter's NPS comments. What are customers actually telling us?"
• "Affinity map these eight interview notes into themes with quotes"
• "Find the themes in our app store reviews and tell me what to fix first"
• "Sales says every prospect wants SSO. Check that against the call notes and churn survey before it goes in the brief"
• "Synthesise this CSAT export into the top customer pain points by segment"

Requests like these belong to a different skill, so it shouldn't answer them:

• "Write me an interview guide for talking to churned customers next week"
• "Map our customer's onboarding journey from sign-up to first invoice, with pains at each stage"
• "Summarise what these five industry reports say about four-day weeks"

If another skill answers instead, ask for this one by name: "use feedback-synthesis".

Check what you get

A good result:

• Every count is distinct people or accounts, computed from the coded items, and says which unit; mentions appear only beside it.
• The ranking puts severity before frequency and says so where the two disagree.
• Every theme title is a falsifiable problem statement naming who and what it costs; no theme is titled with a proposed feature.
• Every quote is verbatim with a source ID; paraphrase never sits inside quotation marks.
• Segments are reported per theme, and a one-segment theme is called out.
• Each source's sampling bias is named, and no percentage of the whole user base is drawn from a self-selected sample.
• What people value and where the sources disagree are both present.
• Interview questions are tied to themes, open, and include one that could disconfirm the top theme.
• Nothing is invented: no quote, count, segment, reason or customer that isn't in the input.

See a worked example

• booking app feedback

Use something else when

• Planning or running the interviews themselves, or writing the question guide — requirements-interview
• Mapping the stages of a journey a customer goes through — user-journey-map
• Answering a research question from papers, reports or articles — source-synthesis
• Ranking rival explanations for a metric change ("why did churn rise in March?") — hypothesis-comparison
• Turning agreed findings into a brief for a PRD or design doc — brief-intake
• Cleaning up a tracker backlog: duplicates, stale tickets, ordering — backlog-triage

Where a loop runs it

• Stage gather of the discover loop

Next

• SKILL.md, the instructions the agent reads
• Its page on the site
• Related: backlog-triage, brief-intake, hypothesis-comparison, requirements-interview, source-synthesis, user-journey-map

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