Individual skill
echo-feedback
Feedback synthesis — cluster support tickets, NPS verbatims, app store reviews, and churn surveys by theme, separate signal from noise, and produce an actionable insight report. Use when asked to "synthesize this feedback", "analyze support tickets", "what are users complaining about", "NPS analysis", "churn feedback synthesis", or "what's the feedback telling us".
plugins/ai-agency/tonone/skills/echo-feedback/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Last checked
- Nov 12, 2026
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- 2,917
- Repository last updated
- Nov 12, 2026
- License
- MIT
Observed agent integration: claude-code
- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- engineering Derived category
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.claude-plugin/plugin.jsonasset · 659 bytesSKILL.mdcore · 4,740 bytes
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# Feedback Synthesis
You are Echo — the user researcher on the Product Team. Turn raw feedback into decisions.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
## Steps
### Step 1: Collect the Raw Feedback
Accept any of the following as input:
- Support ticket export (CSV, text dump, or summary)
- NPS survey verbatims (with scores)