vaibhav0806/startup-skill-pack · Archived

startup-metrics

Define, reconcile, and analyze startup metrics, funnels, cohorts, retention, experiments, and product-market-fit evidence.

First seen Aug 19, 2026

Installation

$ npx skills add vaibhav0806/startup-skill-pack --skill startup-metrics

Summary

  • Define, reconcile, and analyze startup metrics, funnels, cohorts, retention, experiments, and product-market-fit evidence.
  • Use when founders need decision-grade measurement or conflicting numbers resolved; do not use generic benchmarks without matching the business model, stage, segment, and metric definition.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

License LICENSE
Default branch main
Open issues 0
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,936 B
  • docs SUMMARY.md 334 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Startup Metrics

Make the decision and definition explicit before interpreting a number.

Workflow

  1. Establish the business model, stage, decision, user journey, and natural value interval.
  2. Read [metric-system.md](references/metric-system.md) to define metrics and sources before analysis.
  3. When values appear inconsistent or are presented for comparison, keep them both, compare definition, entity, cohort, window, source, and as-of date, classify their relationship, and assign any necessary reconciliation.
  4. Read [cohorts-experiments.md](references/cohorts-experiments.md) for retention, segmentation, or tests.
  5. Read [pmf-evidence.md](references/pmf-evidence.md) before making a product-market-fit claim.
  6. Return the diagnosis, confidence, limitations, missing instrumentation, proposed action, owner, and review date. If ownership is not established, use owner: unassigned; if a calendar date would be invented, use an evidence-based review trigger such as “after the cohort reaches the defined observation window.”

Boundaries

  • A metric without a definition, source, and as-of date is provisional.
  • Do not average values with different definitions or windows.
  • Missing attribution or instrumentation is a finding and an owned corrective action, not permission to infer.
  • Route unexplained customer behavior to customer-discovery, strategic implications to startup-strategy, and weekly commitments to founder-operations.
  • Obtain authorization before changing production instrumentation, billing, live dashboards, or external reporting.