Low CSAT scores tell you something is wrong but not what. Reading every bad survey comment to find the pattern is a job nobody has time for, so the same complaints repeat quarter after quarter.
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Claude
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README.md
Why this subagent
Low CSAT scores tell you something is wrong but not what. Reading every bad survey comment to find the pattern is a job nobody has time for, so the same complaints repeat quarter after quarter.
This agent gathers the week's unhappy tickets and clusters them by root cause, ranked by how often each one came up. The support lead gets a digest that names the top three problems with real customer quotes, plus a flag on anything new. You fix the cause instead of apologizing for the symptom.
How it runs
Used at step 01 to kick off the pipeline.
Write
Used at step 01 to kick off the pipeline.
WebFetch
Used at step 01 to kick off the pipeline.
WebSearch
Used at step 01 to kick off the pipeline.
Cluster them by root cause such as slow response, missing feature, or unclear docs.
pending
Rank the clusters by volume and call out any new pattern that appeared this week.
pending
Send a digest to the support lead and append the numbers to a tracking sheet.
pending
Sample output
json
// Sample output
// (generated when the pipeline finishes)
Given the week's low-CSAT tickets, return clusters by root cause with counts, example quotes, and a flag for anything new this week.
Unlock the rest
The full agent definition, install snippet, and starter task are gated for community members.
Members get the full `.md` agent file, the npm / pnpm install one-liners, a starter prompt that we've tuned against real runs, and the open-source repo when this automation ships there. One email, magic link, done.