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Found 10 Skills
Analyze collections of user feedback to identify patterns and themes. Use when you have user feedback from multiple sources that needs synthesis.
Analyze user/customer feedback and produce a User Feedback Analysis Pack (source inventory, normalized feedback table, taxonomy/codebook, themes + evidence, recommendations, and feedback loop). Use for voice of customer, feature request analysis, support ticket synthesis, churn reason synthesis, and survey open-ends.
Help users synthesize and act on customer feedback. Use when someone is analyzing NPS responses, processing support tickets, reviewing user research, synthesizing feedback from multiple channels, or trying to identify patterns in customer input.
Builds feedback collection systems using Superhuman's PMF framework and YC's "talk to users" methodology. Use when implementing NPS surveys, scheduling user interviews, or measuring product-market fit.
Design system feedback for user actions including confirmations, status updates, and notifications.
Search and analyze Reddit content using semantic AI search via reddit-insights.com MCP server. Use when you need to: (1) Find user pain points and frustrations for product ideas, (2) Discover niche markets or underserved needs, (3) Research what people really think about products/topics, (4) Find content inspiration from real discussions, (5) Analyze sentiment and trends on Reddit, (6) Validate business ideas with real user feedback. Triggers: reddit search, find pain points, market research, user feedback, what do people think about, reddit trends, niche discovery, product validation.
Toast notifications, alerts, feedback messages, and their timing. Use when adding user feedback, success messages, or alerts.
When the user wants to analyze, respond to, or improve their app reviews and ratings. Also use when the user mentions "reviews", "ratings", "negative reviews", "how to get more reviews", "review response", or "my rating is dropping". For broader ASO audit, see aso-audit. For retention issues causing bad reviews, see retention-optimization.
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns.
Capture user corrections and feedback after any skill runs, persist them as learned instructions, and silently apply them on future invocations. TRIGGER when: user gives feedback or corrections after a skill runs — e.g. "next time only show top 5", "always use bullet points", "don't include X", "from now on...", "remember to...". Also: "What have you learned about {skill}?", "Show skill tuning", "Clear skill tuning for {skill}"