From 6947f166851ab6b5f9c832df2abd5578379e1271 Mon Sep 17 00:00:00 2001
From: mohitagw15856 <119053560+mohitagw15856@users.noreply.github.com>
Date: Sun, 22 Feb 2026 18:40:47 +0000
Subject: [PATCH] Create SKILL.md

New Skill: multi-source-signal-synthesiser
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+---
+name: multi-source-signal-synthesiser
+description: Synthesises user signals from multiple research sources into a 
+unified insight brief, reconciling conflicting feedback. Use when user has data 
+from multiple sources, needs to "make sense of all this user data", "what are 
+users really telling us", "synthesise our research", or has conflicting feedback 
+from different channels.
+metadata:
+  author: Mohit Aggarwal
+  version: 1.0.0
+  category: discovery
+  tags: [user-research, synthesis, discovery, insights]
+  documentation: https://github.com/mohitagw15856/pm-claude-skills
+---
+# Multi-Source Signal Synthesiser Skill
+
+## Purpose
+Reconcile user signals from multiple sources — interviews, support tickets, NPS, 
+app reviews, sales calls — into a unified, weighted insight brief that surfaces 
+the underlying need rather than the surface-level request.
+
+## Source Weighting (default — adapt to your context)
+- Direct research (interviews, usability tests): weight 5
+- Support tickets (unprompted pain signals): weight 4
+- NPS verbatims: weight 3
+- App store reviews: weight 2
+- Sales call summaries (filtered through sales lens): weight 2
+- Anecdote or single report: weight 1
+
+## Process
+1. Accept inputs from any combination of the source types above
+2. Tag each signal by source and apply weight
+3. Look for CONVERGENCE: same underlying need appearing across 3+ sources
+4. Look for DIVERGENCE: contradictory signals suggesting user segmentation
+5. Distinguish surface request from underlying need
+   (e.g. "faster export" may mean "I don't trust the data will be there when 
+   I need it")
+6. Produce ranked insights by weighted frequency
+
+## Output Format
+
+### User Signal Synthesis — [Date / Period]
+**Sources included:** [list]
+**Total signals processed:** [n]
+
+#### Insight 1: [Underlying need, not feature request]
+- **Confidence:** High / Medium / Low (based on source diversity and weight)
+- **Evidence:** [Signals from each source supporting this]
+- **Conflicting signals:** [Any contradicting evidence and how to interpret it]
+- **Product implication:** [Specific, not generic]
+
+[Repeat for top 3-5 insights]
+
+#### Divergent Signals (Possible Segmentation)
+[Where user groups appear to have genuinely different needs]
+
+#### What the Data Does NOT Tell Us
+[Gaps that require further research before acting]
+
+## OpenClaw Configuration
+Connect to: Notion (research docs), support inbox, NPS tool, app review feed.
+Schedule: weekly synthesis run, diff output showing new signals only.