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Ra engagement tracker

Skill stephenrogan/augmented-csm/skills/pillar-7-relationship-architecture/ra-engagement-tracker

38 agent skills for the complete CSM operational surface area. Built to the Agent Skills open standard.

Install
npx -y skills add stephenrogan/augmented-csm --skill ra-engagement-tracker

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Tracks touchpoint frequency and recency across all channels for every stakeholder at every account. Computes engagement health per contact, detects declining patterns, and identifies accounts where the relationship is cooling before the health score reflects it. Use when asked to track customer engagement, monitor touchpoint cadence, identify engagement gaps, assess relationship activity, or when any workflow needs to know how recently and how frequently the CSM is engaging with their accounts. Also triggers for questions about touchpoint cadence, engagement health, contact activity, relationship frequency, or communication gaps.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Engagement Tracker

Tracks touchpoint frequency and recency across all communication channels for every stakeholder. Computes engagement health per contact and per account. Part of the Relationship Architecture pillar.

This is a measurement and alerting skill. It tracks frequency -- how often and how recently have you engaged. It does not assess quality -- a weekly call where nothing meaningful is discussed scores the same as a weekly call that transforms the relationship. Frequency is necessary for healthy relationships; it is not sufficient. The CSM provides the quality assessment.

When to Run

  • Continuous: Logs touchpoints as they occur from connected channels
  • Scheduled: Weekly engagement health computation and gap detection
  • On-demand: When a CSM requests engagement data for a specific account or contact

Core Execution Logic

Step 1: Log Touchpoints from All Channels

Every customer interaction is a touchpoint. Capture from all available sources:

ChannelSourceWhat Counts as a TouchpointWhat Does Not Count
EmailEmail integrationEmails sent to or received from a customer contact (excluding automated sequences)Auto-replies, system notifications, marketing emails
MeetingCalendar integrationCompleted meetings with customer attendees (not cancelled, not no-showed)Internal-only meetings, cancelled meetings
CallCall platform or CRM activityCompleted phone/video calls with customer contactsVoicemails left without conversation, abandoned calls
SupportSupport platformTicket interactions where the CSM or customer exchanges substantive communicationAutomated ticket status updates, system notifications
CommunityCommunity platform (if ca-community-monitor is active)Customer posts or replies in the communityPassive viewing without posting
ProductProduct analyticsPortal login or feature usage (passive engagement -- tracked but weighted differently)API calls, automated syncs, background processes

For each touchpoint, log:

  • Timestamp
  • Channel
  • Direction: inbound (customer-initiated) or outbound (CSM-initiated)
  • Contact(s) involved
  • Type: scheduled (planned touchpoint) or unscheduled (ad hoc)

Step 2: Compute Per-Contact Engagement Metrics

For each contact in ra-stakeholder-mapper:

MetricComputationWhy It Matters
Days since last touchCalendar days from most recent touchpoint to todayRecency -- is the relationship current?
Average touchpoint frequencyMean days between touchpoints over trailing 90 daysCadence -- how often are you engaging?
Touchpoint trendFrequency this 30-day period vs. previous 30-day periodDirection -- is engagement increasing, stable, or declining?
Channel distributionPercentage of touchpoints per channelDiversity -- single-channel engagement (email only) is less robust than multi-channel
Inbound ratioInbound touchpoints / total touchpointsReciprocity -- a high inbound ratio suggests the customer is engaged. A zero inbound ratio suggests you are chasing
Response latencyAverage time from CSM outreach to customer responseResponsiveness -- increasing latency is an early cooling signal

Step 3: Classify Engagement Health

For each contact, compare engagement metrics against the expected cadence for their stakeholder type (from ra-stakeholder-mapper):

Health LevelCriteriaSignal
StrongLast touch within expected cadence. Trend stable or improving. Inbound ratio >0.3. Multi-channelRelationship is active and reciprocal
AdequateLast touch within expected cadence but one or more secondary metrics weakening (declining trend, single-channel, low inbound)Relationship is maintained but showing early signs of cooling
DecliningLast touch within 1.5x expected cadence. Trend declining for 2+ consecutive periods. Or inbound ratio dropped to zeroRelationship is cooling. Not yet a gap but heading there without intervention
GapLast touch >2x expected cadenceContact is not being managed. Coverage has lapsed
LostNo engagement across any channel in 90+ daysContact may have left, changed roles, or fully disengaged. Route to ra-stakeholder-change-detector for investigation

Step 4: Compute Per-Account Engagement Health

Aggregate contact-level health into an account-level engagement score:

Weighted by stakeholder type:

  • Champion engagement: 35% weight (the most important relationship)
  • Economic Buyer engagement: 25% weight
  • Executive Sponsor engagement: 15% weight
  • Technical Lead engagement: 15% weight
  • All other contacts: 10% weight

Account engagement score = weighted sum of contact engagement scores (each contact scored 0-100 based on health level: Strong=90, Adequate=70, Declining=45, Gap=20, Lost=0)

Account engagement classification:

ScoreClassificationInterpretation
75-100Healthy engagementKey contacts are actively engaged. Cadence is being maintained
55-74Adequate engagementMost contacts engaged but some weakening. Monitor and address gaps
35-54Declining engagementMeaningful engagement gaps exist. Investigate and intervene
0-34Critical engagement failureMultiple key contacts disengaged. Relationship infrastructure is at risk

Step 5: Detect Patterns and Generate Alerts

PatternDetectionAlert
No-reply streak3+ outbound emails to the same contact with no responseCSM alert: "[Contact] has not responded to last 3 emails. Consider calling or approaching through a different contact"
Meeting cancellation pattern2+ meetings cancelled or no-showed by the same contact in 30 daysCSM alert: "[Contact] cancelled or missed 2+ meetings. Engagement is declining"
Inbound engagement dropAccount's inbound ratio drops from >0.3 to <0.1 over 60 daysCSM alert: "[Account] has stopped initiating contact. All recent touchpoints are outbound"
Champion coolingChampion contact moves from Strong to Declining engagement healthCSM + manager alert: "Champion [name] engagement declining at [account]. [Specific metrics]"
Complete silenceZero touchpoints across all channels for an account in 30+ daysCSM alert: "[Account] has had no engagement of any kind in [X] days. Investigate immediately"

Step 6: Generate Engagement Report

Per-CSM weekly engagement summary:

{
  "csm": "Jane Doe",
  "report_date": "2026-03-10",
  "portfolio_engagement": {
    "total_accounts": 42,
    "engagement_distribution": {
      "healthy": 28,
      "adequate": 8,
      "declining": 4,
      "critical": 2
    },
    "avg_engagement_score": 72
  },
  "alerts_this_week": [
    {
      "type": "no_reply_streak",
      "account": "Gamma Corp",
      "contact": "Lisa Park (VP Eng)",
      "detail": "3 outbound emails in 14 days with no response",
      "recommended_action": "Try a different channel (call) or approach through another contact"
    },
    {
      "type": "champion_cooling",
      "account": "Beta Inc",
      "contact": "Tom Chen (Champion)",
      "detail": "Engagement moved from Strong to Declining. Touchpoint frequency down from every 10 days to every 28 days over last 60 days",
      "recommended_action": "Investigate. Schedule a direct conversation. Do not add more emails to the no-reply streak"
    }
  ],
  "engagement_movers": {
    "improved": [
      { "account": "Acme Corp", "score_change": "+12", "driver": "Executive sponsor engaged for first time in 90 days" }
    ],
    "declined": [
      { "account": "Beta Inc", "score_change": "-15", "driver": "Champion engagement cooling" }
    ]
  },
  "cadence_compliance": {
    "touchpoints_expected": 38,
    "touchpoints_completed": 34,
    "compliance_rate": 0.89,
    "overdue_touchpoints": [
      { "account": "Delta Ltd", "contact": "Sarah Kim", "expected_cadence": "monthly", "days_overdue": 12 }
    ]
  }
}

Handoff to Human

Decision PointContext ProvidedWhat the Human Decides
Declining engagement responseSpecific contacts, metric trends, pattern detailsHow to respond -- call, email, approach through another contact, escalate to manager, or wait. The approach depends on the relationship
No-reply interpretationStreak length, contact role, prior engagement patternWhether the silence means disengagement, a busy period, a personnel change, or deliberate avoidance. Each has a different response
Cadence adjustmentCurrent engagement frequency vs. expected cadenceWhether the expected cadence is right for this contact. Some contacts prefer less frequent engagement. The cadence rules are defaults, not mandates
Engagement quality assessmentFrequency and recency dataWhether the touchpoints are meaningful. A CSM meeting weekly with a customer but never advancing the relationship has a perfect engagement score and a failing relationship. The human layer is essential
Alert triageMultiple alerts across the portfolioWhich declining engagements to address first, given limited CSM time and competing priorities

Confidence and Limitations

  • High confidence for touchpoint logging and frequency computation -- structured event data from connected systems
  • High confidence for engagement health classification -- deterministic comparison of metrics to defined thresholds
  • Medium confidence for pattern detection (no-reply streaks, cancellation patterns) -- these are reliable signals but have multiple possible interpretations
  • Medium confidence for inbound ratio as an engagement quality proxy -- a declining inbound ratio is a meaningful signal, but some customers are naturally passive communicators. Benchmark against the contact's own historical pattern, not a universal standard
  • Low confidence for engagement quality assessment. This is the fundamental limitation: the skill tracks frequency, not depth. A 15-minute status call and a 2-hour strategic planning session count the same. The CSM provides the quality layer
  • Cannot track engagement that happens outside connected systems (in-person meetings, conferences, informal conversations, personal phone calls)
  • "No inbound engagement" is a strong disengagement signal in most cases, but some customers only engage reactively and have always done so. The baseline matters more than the absolute number

Dependencies

Required:

  • CRM API (activity data, contact records)
  • Calendar integration (meeting data)
  • Email integration (email activity data)

Strongly recommended:

  • ra-stakeholder-mapper (stakeholder types and expected cadence for health computation)
  • Call platform integration (call data)
  • Support platform (support interaction data)
  • ca-community-monitor (community engagement channel)

Downstream consumers:

  • bi-health-score (engagement data feeds the engagement component -- 25% default weight)
  • ra-stakeholder-mapper (engagement status per contact)
  • bi-risk-detector (declining engagement as a risk signal)
  • lo-check-in-scheduler (cadence compliance data)
  • cc-report-generator (engagement metrics for CSM and manager reports)

References

  • references/engagement-methodology.md -- Channel definitions, health classification thresholds, and cadence baseline calibration

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Said here and by no other author read

  • log touchpoints from all connected channels
  • compute per-contact engagement metrics
  • classify contact engagement health
  • detect declining engagement patterns
  • exclude automated emails from touchpoints
  • weight champion engagement highest in account scores

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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