pa-adoption-tracker — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited pa-adoption-tracker (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.
Tracks feature-level product adoption within accounts. Maps used vs. available features, identifies underutilisation, and generates gap analysis to feed adoption planning. Part of the Product Adoption & Value Realisation pillar.
This is a measurement and analysis skill. It tells you what the customer is using and what they are not. It does not diagnose why adoption has stalled (that is often organisational, not technical -- a human judgment) or build the adoption strategy (that is consultative work).
For each account, determine the total available feature set:
references/feature-catalogue.md)For each available feature, query product analytics for:
| Metric | Definition | Measurement Period |
|---|---|---|
| Ever used | Has any user at this account ever used this feature | All time |
| Active users | Number of distinct users who used the feature | Last 30 days |
| Usage frequency | How often the feature is used per active user | Last 30 days |
| Last used date | Most recent usage of the feature by any user | Timestamp |
| Trend | Usage direction compared to 90-day baseline | Current vs. 90-day avg |
For each feature, classify based on usage depth:
| Status | Criteria | What It Means |
|---|---|---|
| Core adopted | Used by >50% of active users, weekly or more frequently | Feature is embedded in the team's workflow. Switching cost is high |
| Partially adopted | Used by 10-50% of users, or used monthly or less | Feature is known but not habitual. Adoption can deepen or fade |
| Explored | Used by <10% of users, or used fewer than 3 times total | Someone tried it. It did not stick. Investigate why |
| Abandoned | Previously used (>5 uses historical) but no usage in 60+ days | Feature was adopted then dropped. This is a stronger signal than "never used" -- something changed |
| Untouched | Never used by any user | Customer may not know it exists, may not need it, or may face a barrier to adopting it |
For each untouched, explored, or abandoned feature:
Rank gaps by:
For each recommended gap to address, include:
Per-account adoption profile:
{
"account_id": "string",
"product_tier": "professional",
"scan_date": "2026-03-10",
"features_available": 24,
"adoption_summary": {
"core_adopted": 12,
"partially_adopted": 5,
"explored": 3,
"abandoned": 1,
"untouched": 3
},
"adoption_score": 0.71,
"adoption_trend": "stable",
"top_gaps": [
{
"feature": "Advanced Reporting",
"feature_group": "Analytics",
"status": "untouched",
"segment_adoption_rate": 0.78,
"relevance": "high",
"goal_alignment": "Customer goal: reduce manual reporting time. This feature automates executive report generation",
"value_estimate": "4-6 hours per week saved for the analytics team",
"recommended_approach": "Live demo in next check-in -- feature is complex enough to warrant guided introduction",
"priority": 1
},
{
"feature": "Workflow Automation Rules",
"feature_group": "Automation",
"status": "abandoned",
"last_used": "2025-11-15",
"segment_adoption_rate": 0.65,
"relevance": "high",
"goal_alignment": "Customer previously used this. Abandonment coincides with their admin leaving in November",
"value_estimate": "Eliminates 3 manual steps per workflow execution",
"recommended_approach": "Investigate abandonment cause with current admin. May need re-training after personnel change",
"priority": 2
}
],
"portfolio_position": {
"vs_segment_median": "above",
"percentile": 68,
"trend": "stable"
}
}Portfolio adoption report (weekly):
{
"report_date": "2026-03-10",
"portfolio_summary": {
"total_accounts": 42,
"avg_adoption_score": 0.64,
"accounts_above_median": 24,
"accounts_below_25th": 6,
"features_most_underutilised": [
{ "feature": "Advanced Reporting", "untouched_accounts": 18, "segment_adoption_rate": 0.78 }
]
},
"movers": {
"adoption_improved": [{ "account": "Acme Corp", "score_change": "+0.08", "features_newly_adopted": 2 }],
"adoption_declined": [{ "account": "Beta Inc", "score_change": "-0.05", "features_abandoned": 1 }]
}
}| Decision Point | Context Provided | What the Human Decides |
|---|---|---|
| Gap prioritisation | Ranked gaps with relevance, peer data, and value estimate | Which gaps to address first based on customer relationship context and conversation timing |
| Abandonment investigation | Feature name, abandonment date, correlated events | Whether to investigate with the customer, and how to frame it |
| Adoption plan creation | Gap analysis, enablement resources, peer benchmarks | The actual adoption plan -- milestones, timeline, how to position it with the customer |
| Enablement approach | Self-serve vs. guided recommendation per gap | Whether the customer needs a demo, a training session, or just a link |
| Product feedback | Adoption gaps that persist despite enablement | Whether to escalate to product as a UX or capability issue |
Required:
references/feature-catalogue.md)Strongly recommended:
Downstream consumers:
references/feature-catalogue.md -- Feature definitions, tier mapping, categorisation, and maintenance process~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.