Feedback prioritizer

Skill varunk130/ai-customer-discovery-skills/skills/feedback-prioritizer

12 AI-powered skills for product discovery — from raw customer signal to validated opportunity. Built for Claude Code & GitHub Copilot.

Install

npx -y skills add varunk130/ai-customer-discovery-skills --skill feedback-prioritizer

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Triages a backlog of raw customer feedback into a ranked list of opportunities scored on reach, severity, strategic fit, and confidence. Outputs a prioritized list with explicit "do not act" callouts for vocal-minority signals. Use when: triage feedback, prioritize feature requests, customer feedback backlog, what should we build next, opportunity scoring, RICE feedback, feedback synthesis.

SKILL.md

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Feedback Prioritizer

Convert a stack of customer feedback (tickets, interview notes, NPS comments, sales loss reasons) into a small ranked list of opportunities, with explicit reasoning for what not to act on. The single most important section of the output is "Do Not Act" - vocal-minority signals that look compelling but would distract the roadmap.

Core Principle

Most feedback is noise; the prioritizer's job is to find the signal and name the noise. A ranked list without a "Do Not Act" section silently licenses the team to chase the loudest voices.

Scoring Model: RSCF

Each candidate opportunity is scored 1-5 on four dimensions:

Letter	Dimension	Question
R	Reach	What share of paying customers will benefit?
S	Severity	When the problem hits, how badly does it hurt?
C	Strategic fit	Does this align with the current strategy or pull us off-mission?
F	Confidence	How certain are we, given evidence quality and quantity?

Score = R × S × C × F / 25 (normalized to 0-25). Confidence acts as a multiplier that crushes weakly-evidenced items.

Output

Save to outputs/feedback-priority-[period]-[YYYY-MM-DD].md

Section	Description
Top 5 Opportunities	Ranked by RSCF, with evidence count and source breakdown
Watch List	Promising but evidence-light items (Confidence ≤ 2) - gather more data
Do Not Act	Vocal-minority signals with explicit reasoning for de-prioritization
Patterns Across Sources	Themes that appeared in 3+ independent channels (highest-trust signal)
Counterfactual Check	"If we only did the top-1 item, would the next quarter look meaningfully better?"

Process

Step 1: Intake

I'll ask:

"Share the feedback corpus (paste, file, or sample). Tell me the time window, source mix (tickets / interviews / NPS / sales / churn), and your current strategy in one sentence."

Step 2: Cluster

Group raw items into themes. Items that repeat across different sources weight more than the same item repeated 50× from one source.

Step 3: Score

Score each theme 1-5 on R, S, C, F with a one-line rationale per dimension. Compute RSCF.

Step 4: Pattern Pass

Surface themes that appeared in 3+ source types - these are the highest-trust signals even if individual scores are middling.

Step 5: Build the Do-Not-Act List

Identify items that:

Came from a single loud source
Conflict with strategy (low C)
Would require disproportionate effort relative to RSCF For each, write why it's tempting and why it's wrong.

Step 6: Counterfactual

Test the top-1 against the question: "If this is all we shipped next quarter, is the quarter visibly better?" If no, re-open the ranking.

Tips

Source diversity beats source volume. 3 channels saying the same thing is stronger than 30 customers saying it on one.
Confidence is the multiplier that matters. A 4×4×4×1 scores 16; a 3×3×3×4 scores 27. Evidence quality wins.
Always publish the Do Not Act list. It's the only section that protects strategic focus.