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Rep performance tracker

Skill koinod/koino-skills/rep-performance-tracker

Free AI agent skills for business automation. Sales, content, ops, growth. Compatible with Claude Code, Codex, Gemini CLI, Cursor.

Install
npx -y skills add koinod/koino-skills --skill rep-performance-tracker

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SKILL.md

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Rep Performance Tracker

Track sales rep metrics: calls, close rate, pipeline value, and churn risk scoring.

Description

Rep Performance Tracker turns raw sales activity data into actionable performance dashboards. It calculates close rates, pipeline velocity, activity ratios, and flags reps at risk of churning or underperforming — before it shows up in revenue. Works for solo operators tracking their own metrics or managers overseeing a team.

Activation

This skill activates when:

  • The user wants to track or analyze sales performance metrics
  • The user provides sales activity data (calls, closes, pipeline)
  • The user asks about close rates, conversion rates, or sales efficiency
  • The user mentions rep performance, sales leaderboard, or activity tracking

Trigger phrases: "track my sales", "close rate", "rep performance", "sales metrics", "pipeline velocity", "how am I doing", "sales dashboard", "conversion rate", "activity report"

Core Metrics

Activity Metrics (Leading Indicators)

MetricFormulaBenchmark
Calls/DayTotal calls / days worked25-50 (outbound), 10-20 (closing)
Emails Sent/DayTotal emails / days worked30-60 (SDR), 10-20 (AE)
Meetings Booked/WeekMeetings scheduled per week5-10 (SDR), 8-15 (AE)
Talk Time/DayMinutes on calls per day120-180 min (outbound)
Activity ScoreWeighted sum of all activities0-100 scale

Conversion Metrics (Process Indicators)

MetricFormulaBenchmark
Lead → MeetingMeetings / leads contacted5-15% (cold), 20-40% (inbound)
Meeting → ProposalProposals / meetings held40-60%
Proposal → CloseCloses / proposals sent25-40%
Full FunnelCloses / total leads2-5% (cold), 10-20% (inbound)
Speed to LeadAvg minutes to first response<5 min = best in class

Revenue Metrics (Lagging Indicators)

MetricFormulaBenchmark
Revenue/MonthTotal closed revenueRole-dependent
Avg Deal SizeRevenue / deals closedIndustry-dependent
Pipeline ValueSum of weighted opportunities3-5x monthly quota
Pipeline Velocity(Deals x Win% x Avg Size) / Cycle DaysHigher = better
Revenue per ActivityRevenue / total activitiesEfficiency measure

Instructions

When given sales data, generate:

## Rep Performance Report: [Name]
### Period: [Date Range]

---

### SCORECARD

| Category | Metric | Actual | Target | Status |
|----------|--------|--------|--------|--------|
| Activity | Calls/day | XX | XX | [on/above/below] |
| Activity | Emails/day | XX | XX | [on/above/below] |
| Activity | Meetings/week | XX | XX | [on/above/below] |
| Conversion | Lead → Meeting | XX% | XX% | [on/above/below] |
| Conversion | Meeting → Proposal | XX% | XX% | [on/above/below] |
| Conversion | Proposal → Close | XX% | XX% | [on/above/below] |
| Revenue | MTD Revenue | $XX | $XX | [on/above/below] |
| Revenue | Pipeline Value | $XX | $XX | [on/above/below] |
| Revenue | Avg Deal Size | $XX | $XX | [on/above/below] |

### PERFORMANCE GRADE: [A/B/C/D/F]

### TRENDS (vs. Previous Period)
- Activity: [up/down X%] — [interpretation]
- Conversion: [up/down X%] — [interpretation]
- Revenue: [up/down X%] — [interpretation]

### CHURN RISK: [LOW / MEDIUM / HIGH / CRITICAL]
[Explanation of churn risk assessment]

### TOP RECOMMENDATION
[The single highest-leverage action to improve performance]

Churn Risk Scoring

Applies to tracking rep retention risk (for managers) or client churn risk (for account managers).

SignalPointsWeight
Activity down >20% week-over-week+25High
Missed quota 2+ consecutive months+20High
Response time increasing+15Medium
Pipeline not being replenished+15Medium
Cancellation language in communications+30Critical
Engagement with training/tools declining+10Low
Peer performance significantly higher+10Low
ScoreRisk LevelAction
0-20LOWStandard check-in
21-45MEDIUM1:1 coaching session, identify blockers
46-70HIGHPerformance improvement plan, daily check-ins
71-100CRITICALImmediate intervention, retention conversation

Example

Input

Solo operator. Last 30 days: 47 cold calls, 156 emails, 8 meetings booked, 5 proposals sent, 2 deals closed. Revenue: $6,500. Pipeline: $22,000 across 6 opportunities. Target: $10,000/month. Previous month: 1 deal closed for $3,200.

Output

CategoryMetricActualTargetStatus
ActivityCalls/day2.15BELOW
ActivityEmails/day7.115BELOW
ActivityMeetings/week23BELOW
ConversionLead → Meeting17%10%ABOVE
ConversionMeeting → Proposal63%50%ABOVE
ConversionProposal → Close40%30%ABOVE
RevenueMTD Revenue$6,500$10,000BELOW
RevenuePipeline Value$22,000$30,000BELOW
RevenueAvg Deal Size$3,250$3,000ABOVE

PERFORMANCE GRADE: B-

TRENDS: Revenue up 103% MoM. Conversion rates are strong. Activity volume is the bottleneck — not skill.

CHURN RISK: N/A (solo operator)

TOP RECOMMENDATION: Your conversion rates are elite (40% proposal-to-close is top quartile). The ONLY problem is volume. Increase cold calls from 2/day to 5/day and emails from 7/day to 15/day. At your current conversion rates, that alone puts you at $13K+ next month. Your skill is not the problem — your pipeline is starving.

Team Leaderboard Mode

For managers tracking multiple reps:

| Rank | Rep | Revenue | Close Rate | Activity Score | Trend | Risk |
|------|-----|---------|------------|----------------|-------|------|
| 1 | Sarah | $18,200 | 38% | 92/100 | +12% | LOW |
| 2 | Mike | $14,100 | 31% | 78/100 | +5% | LOW |
| 3 | Alex | $8,400 | 22% | 65/100 | -15% | MEDIUM |
| 4 | Jordan | $3,100 | 12% | 41/100 | -28% | HIGH |

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Said here and by no other author read

  • calculate activity conversion and revenue metrics
  • generate a rep performance report
  • assign a performance grade
  • calculate churn risk using specified signals
  • recommend the highest leverage action
  • generate a team leaderboard for multiple reps

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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