Churn autopsy
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npx -y skills add bg-szy/TOP-SKILLS --skill churn-autopsyAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Post-mortem analysis when a client churns. Takes client history, engagement data, support tickets, usage logs, and exit feedback to produce a comprehensive churn autopsy with root cause classification, timeline of decline, and preventive measures.
SKILL.md
2.0 KB, as published. Nobody here has run it
Churn Autopsy
Dissect a client departure with forensic rigor and produce churn-autopsy.md: a historical record and retention playbook that turns a loss into organizational learning.
Contents
references/inputs.md-- required and optional data to gather before analysisreferences/analysis-framework.md-- the six-phase forensic methodreferences/root-cause-taxonomy.md-- root cause categories and subcategoriesreferences/output-template.md-- fullchurn-autopsy.mdreport structurereferences/standards.md-- objectivity, rigor, sensitivity, incomplete-data, and operating rules
Workflow
- Collect. Gather all available inputs per
references/inputs.md. Read provided files directly; query connected CRM and analytics MCP tools for account, usage, and support data. Note any gaps. - Organize. Build the full chronological timeline from first touch to cancellation before attempting analysis.
- Analyze. Apply the six phases in
references/analysis-framework.mdsystematically, without skipping: baseline, timeline of decline, root cause classification, missed warning signs, counterfactual analysis, lessons learned. - Classify. Assign one primary root cause and any contributing causes using
references/root-cause-taxonomy.md. - Draft. Write the report in the structure defined in
references/output-template.md. - Challenge. Review every conclusion against
references/standards.md; attempt to disprove each finding before keeping it. - Finalize. Produce
churn-autopsy.mdwith all sections complete in the current working directory or a user-specified location.
Gives 0 of the 12 instructions most analytics metrics skills give
Counted across 368 of the 369 authors here whose files we hold, read 2026-08-06
- read product marketing context before asking questionsin 18 of 368, across 12 files
- use lowercase with underscores for event namesin 16 of 368, across 6 files
- track events for decisions not vanity metricsin 15 of 368, across 5 files
- use object-action format for event namesin 15 of 368, across 8 files
- produce a tracking plan documentin 14 of 368, across 4 files
- Call RUBE_SEARCH_TOOLS first to get current schemasin 13 of 368, across 2 files
- establish consistent event naming conventions before implementingin 10 of 368, across 4 files
- Verify dimension and metric compatibility before reportingin 9 of 368, across 2 files
- Encrypt data at rest and in transitin 9 of 368, across 3 files
- use snake_case for event namesin 9 of 368, across 5 files
- monitor technical health during the testin 9 of 368, across 5 files
- use consistent property namesin 8 of 368, across 4 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.