Use to interpret qualitative feedback, trends, and risks across community channels.
NewMaintained
Automatic
◆Customer Success pack
Last verified 8/23/2026
What it changes
Passed 19 of 22 test cases with the skill, and 19 of 22 without it.
Without skill86%
With skill86%
Checks it passed that the model alone missed
The tagging schema includes persona as a taxonomy dimension.
The process pairs sentiment analysis with the measure-engagement command.
2 fixed17 passed either way1 still failing2 broke
Pass-rate lift
0 pp
Tokens
-8%
Agent turns
0%
Response time
-18%
Model gemini-3.6-flashMeasured 8/23/2026v119 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 2
Prompt
When designing a community tagging schema for post-launch sentiment processing, a team member suggested only tracking the topic, sentiment polarity, and severity level. What complete list of categorization dimensions should be included in the tagging taxonomy?
What was checked, without and with the skill
Checked
Without skill
With skill
The tagging schema categorizes sentiment by emotion.
Passed
Passed
The tagging schema includes persona as a taxonomy dimension.
Missed
Passed
case-02 · gemini-3.6-flash · 8/23/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md25 linessingle file
Community Sentiment Analysis Skill
When to Use
Monitoring community tone during launches, incidents, or roadmap changes.
Preparing executive updates that require member sentiment context.
Prioritizing response or enablement efforts based on emerging themes.
Framework
Signal Sources – forums, chat transcripts, surveys, social listening, support tickets.
Tagging Schema – categorize by emotion, topic, product area, persona, and severity.
Trend Analysis – track frequency over time, correlate with launches or incidents.