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zpower426zpower426/pmpowers/skills/metrics-definition/SKILL.md

metrics-definition

Skill0 starsChanged 7 months agoMITView on GitHub

Define, instrument, and track key data points that measure product success, transforming business goals into a quantified feedback loop.

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Proxy Metrics (Behavioral): Search frequency, Share rate.

    line 16
  2. Distinctive:

    Data Consistency: Ensure that the logical meaning of backend tracking aligns with frontend tracking.

    line 22

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Metrics Definition: Quantitative Metrics and Feedback Loops

What cannot be measured cannot be optimized.

Checklist

  1. Define Core Events — Which user actions reflect the delivery of core value?
  2. Develop Instrumentation Plan (Tracking) — Event names, properties, and trigger conditions.
  3. Categorize Metric Attributes —
    • Outcome Metrics: Retention, Revenue.
    • Proxy Metrics (Behavioral): Search frequency, Share rate.
  4. Establish Dashboards — Ensure real-time visibility of data.

Core Mandates

  • Prevent Noise: More tracking is not necessarily better. Every data point tracked must correspond to a specific decision.
  • Data Consistency: Ensure that the logical meaning of backend tracking aligns with frontend tracking.
  • Interpretability: Metrics must be understandable to team members without a data background.

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