Review and analyze product metrics with trend analysis and actionable insights.
SkillScore86Maintained
Automatic
◆Product Management pack
Last verified 8/19/2026
What it changes
Passed 19 of 22 test cases with the skill, and 14 of 22 without it.
Without skill64%
With skill86%
Checks it passed that the model alone missed
Recommends setting between 2 and 4 Key Results per Objective.
Places the North Star metric at the top of the dashboard layout.
States that every alert must be actionable and assigned to an owner.
and 3 more in the full report
5 fixed14 passed either way3 still failing0 broke
Pass-rate lift
+23 pp
Tokens
+138%
Agent turns
0%
Response time
-25%
Model gemini-3.6-flashMeasured 8/19/2026v119 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 5
Prompt
Our team leader is drafting OKRs for our productivity application and wants to assign 8 distinct Key Results to a single Objective to ensure thorough coverage. What is the recommended range for Key Results per Objective in standard product goal-setting frameworks, and why?
What was checked, without and with the skill
Checked
Without skill
With skill
Recommends setting between 2 and 4 Key Results per Objective.
Missed
Passed
case-08 · gemini-3.6-flash · 8/19/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md389 linessingle file
Metrics Review
Review and analyze product metrics, identify trends, and surface actionable insights.
Usage
/pm-metrics-review $ARGUMENTS
Workflow
1. Gather Metrics Data
Pull data from connected sources before asking the user:
Stripe (int-stripe):
MRR, ARR, new revenue, churn, expansion revenue
Subscription changes, plan mix, trial conversions
Licensing (int-licensing):
Active instances, version distribution, geographic spread
Growth trends for open source usage
Evo CRM (int-evo-crm):
Active agents, pipeline metrics, user activity
Activation and engagement signals
If no tool data is available, ask the user to provide:
The metrics and their values (paste a table, screenshot, or describe)
Comparison data (previous period, targets)
Any context on recent changes (launches, incidents, seasonality)
Ask the user:
What time period to review? (last week, last month, last quarter)
What metrics to focus on? Or should we review the full product metrics suite?
Are there specific targets or goals to compare against?
Any known events that might explain changes (launches, outages, marketing campaigns, seasonality)?