retention-analyzer — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited retention-analyzer (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Checks.agents/product-marketing-context.mdfor product context. Checks.agents/growth-metrics-context.mdfor baseline retention. If growth-mcp connected, pulls real cohort data viaanalyze_retentionandpredict_churn_risk. Otherwise, use expert defaults below.
| Metric | Good | Average | Poor |
|---|---|---|---|
| D1 Retention | > 50% | 30-50% | < 30% |
| D7 Retention | > 30% | 15-30% | < 15% |
| D30 Retention | > 20% | 10-20% | < 10% |
| Monthly Churn | < 15% | 15-30% | > 30% |
When retention drops, check:
| Problem | Intervention | Expected Lift |
|---|---|---|
| D1 drop (activation) | Onboarding flow fix, welcome voucher | +5-15% |
| D7 drop (habit) | Push nudge series, streak reward | +3-10% |
| D30 drop (churn risk) | Re-engagement campaign, winback voucher | +2-8% |
| General decay | Loyalty program, points economy | +5-20% over 3 months |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.