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Found 23 Skills
Use when users don't notice feedback, miss state changes, or can't tell if their action worked
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.
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.
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.
Create and configure surveys in PostHog through guided conversation. Use this skill when a user wants to create a survey, collect user feedback, run NPS/CSAT/CES/PMF surveys, gather product feedback, or understand user sentiment. The skill guides Product Managers through survey design by matching their goals to proven templates (or creating custom surveys), then configuring targeting and scheduling before creating via PostHog MCP tools.
Design system feedback for user actions including confirmations, status updates, and notifications.
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}"
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.
Toast notifications, alerts, feedback messages, and their timing. Use when adding user feedback, success messages, or alerts.
Help users de-risk new product bets by testing core assumptions, building low-fidelity prototypes, and gathering high-signal evidence before investing heavy engineering resources.
Focused Signals scout for PostHog projects running surveys. Watches active surveys for score regressions (NPS / CSAT / rating drops), response-volume drops, abandonment spikes, and targeting drift, AND aggregates open-text responses into recurring themes the team should know about (clusters of complaints, praise, feature requests). Emits findings only when a theme or anomaly clears the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet — no dependencies on other skills.