solo-metrics-track

Set up PostHog metrics plan with event funnel, KPI benchmarks, and kill/iterate/scale decision thresholds. Use when user says "set up metrics", "track KPIs", "PostHog events", "funnel analysis", "when to kill or scale", or "success metrics". Do NOT use for SEO metrics (use /seo-audit).

16 stars

Best use case

solo-metrics-track is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Set up PostHog metrics plan with event funnel, KPI benchmarks, and kill/iterate/scale decision thresholds. Use when user says "set up metrics", "track KPIs", "PostHog events", "funnel analysis", "when to kill or scale", or "success metrics". Do NOT use for SEO metrics (use /seo-audit).

Teams using solo-metrics-track should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/solo-metrics-track/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/business/solo-metrics-track/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/solo-metrics-track/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How solo-metrics-track Compares

Feature / Agentsolo-metrics-trackStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Set up PostHog metrics plan with event funnel, KPI benchmarks, and kill/iterate/scale decision thresholds. Use when user says "set up metrics", "track KPIs", "PostHog events", "funnel analysis", "when to kill or scale", or "success metrics". Do NOT use for SEO metrics (use /seo-audit).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# /metrics-track

Set up a metrics tracking plan for a project. Defines PostHog event funnel, KPI benchmarks, and kill/iterate/scale decision thresholds based on lean startup principles.

## MCP Tools (use if available)

- `kb_search(query)` — find PostHog methodology, analytics patterns

If MCP tools are not available, fall back to Grep + Read.

## Methodology Reference

This skill implements metrics tracking based on lean startup principles:
- **Relative metrics vs niche benchmarks** — compare against your own trajectory, not vanity averages
- **Kill/iterate/scale decision rules** — data-driven thresholds for product decisions (see step 7 below)

## Steps

1. **Parse project** from `$ARGUMENTS`.
   - Read PRD for features, ICP, monetization model.
   - Read CLAUDE.md for stack (iOS/Web/both).
   - If empty: ask via AskUserQuestion.

2. **Detect platform:**
   - iOS app → PostHog iOS SDK events
   - Web app → PostHog JS SDK events
   - Both → cross-platform identity (shared user ID across platforms)

3. **Load PostHog methodology:**
   - If MCP available: `kb_search("PostHog analytics events funnel identity")`
   - Otherwise: check project docs for existing analytics configuration
   - Extract: event naming conventions, identity resolution, funnel pattern

4. **Define event funnel** based on PRD features:

   Standard funnel stages (adapt per product):
   ```
   Awareness → Acquisition → Activation → Revenue → Retention → Referral
   ```

   Map to concrete events:

   | Stage | Event Name | Trigger | Properties |
   |-------|-----------|---------|------------|
   | Awareness | `page_viewed` | Landing page visit | `source`, `utm_*` |
   | Acquisition | `app_installed` or `signed_up` | First install/signup | `platform`, `source` |
   | Activation | `core_action_completed` | First key action | `feature`, `duration_ms` |
   | Revenue | `purchase_completed` | First payment | `plan`, `amount`, `currency` |
   | Retention | `session_started` | Return visit (D1/D7/D30) | `session_number`, `days_since_install` |
   | Referral | `invite_sent` | Shared or referred | `channel`, `referral_code` |

5. **Forced reasoning — metrics selection:**
   Before defining KPIs, write out:
   - **North Star Metric:** The ONE number that matters most (e.g., "weekly active users who completed core action")
   - **Leading indicators:** What predicts the North Star? (e.g., "activation rate D1")
   - **Lagging indicators:** What confirms success? (e.g., "MRR", "retention D30")
   - **Vanity metrics to AVOID:** (e.g., total downloads without activation)

6. **Set KPI benchmarks** per stage:

   | KPI | Target | Kill Threshold | Scale Threshold | Source |
   |-----|--------|---------------|-----------------|--------|
   | Landing → Signup | 3-5% | < 1% | > 8% | Industry avg |
   | Signup → Activation | 20-40% | < 10% | > 50% | Product benchmark |
   | D1 Retention | 25-40% | < 15% | > 50% | Mobile avg |
   | D7 Retention | 10-20% | < 5% | > 25% | Mobile avg |
   | D30 Retention | 5-10% | < 2% | > 15% | Mobile avg |
   | Trial → Paid | 2-5% | < 1% | > 8% | SaaS avg |

   Adjust based on product type (B2C vs B2B, free vs paid, mobile vs web).

7. **Define decision rules** (lean startup kill/iterate/scale):

   ```markdown
   ## Decision Framework

   **Review cadence:** Weekly (Fridays)

   ### KILL signals (any 2 = kill)
   - [ ] Activation rate < {kill_threshold} after 2 weeks
   - [ ] D7 retention < {kill_threshold} after 1 month
   - [ ] Zero organic signups after 2 weeks of distribution
   - [ ] CAC > 3x LTV estimate

   ### ITERATE signals
   - [ ] Metrics between kill and scale thresholds
   - [ ] Qualitative feedback suggests product-market fit issues
   - [ ] One stage of funnel is dramatically worse than others

   ### SCALE signals (all 3 = scale)
   - [ ] Activation rate > {scale_threshold}
   - [ ] D7 retention > {scale_threshold}
   - [ ] Organic growth > 10% week-over-week
   ```

8. **Generate PostHog implementation snippets:**

   ### For iOS (Swift):
   ```swift
   // Event tracking examples
   PostHogSDK.shared.capture("core_action_completed", properties: [
       "feature": "scan_receipt",
       "duration_ms": elapsed
   ])
   ```

   ### For Web (TypeScript):
   ```typescript
   // Event tracking examples
   posthog.capture('signed_up', {
       source: searchParams.get('utm_source') ?? 'direct',
       plan: 'free'
   })
   ```

9. **Write metrics plan** to `docs/metrics-plan.md`:

   ```markdown
   # Metrics Plan: {Project Name}

   **Generated:** {YYYY-MM-DD}
   **Platform:** {iOS / Web / Both}
   **North Star:** {north star metric}

   ## Event Funnel

   | Stage | Event | Properties |
   |-------|-------|------------|
   {event table from step 4}

   ## KPIs & Thresholds

   | KPI | Target | Kill | Scale |
   |-----|--------|------|-------|
   {benchmark table from step 6}

   ## Decision Rules

   {framework from step 7}

   ## Implementation

   ### PostHog Setup
   - Project: {project name} (EU region)
   - SDK: {posthog-ios / posthog-js}
   - Identity: {anonymous → identified on signup}

   ### Code Snippets
   {snippets from step 8}

   ## Dashboard Template
   - Funnel: {stage1} → {stage2} → ... → {stageN}
   - Retention: D1 / D7 / D30 cohort chart
   - Revenue: MRR trend + trial conversion

   ---
   *Generated by /metrics-track. Implement events, then review weekly.*
   ```

10. **Output summary** — North Star metric, key thresholds, first event to implement.

## Notes

- PostHog EU hosting for privacy compliance
- Use `$set` for user properties, `capture` for events
- Identity: start anonymous, `identify()` on signup with user ID
- Cross-platform: same PostHog project, same user ID → unified journey
- Review dashboard weekly, make kill/iterate/scale decision monthly

## Common Issues

### Wrong platform detected
**Cause:** Project has both web and iOS indicators.
**Fix:** Skill checks package manifests. If both exist, it generates cross-platform identity setup. Verify the detected platform in the output.

### KPI thresholds too aggressive
**Cause:** Default thresholds are industry averages.
**Fix:** Adjust thresholds in `docs/metrics-plan.md` based on your niche. B2B typically has lower volume but higher conversion.

### PostHog SDK not in project
**Cause:** Metrics plan generated but SDK not installed.
**Fix:** This skill generates the PLAN only. Install PostHog SDK separately: `pnpm add posthog-js` (web) or add `posthog-ios` via SPM (iOS).

Related Skills

ML Experiment Tracking

16
from diegosouzapw/awesome-omni-skill

Track machine learning experiments with reproducible parameters and metrics

daily-work-tracker

16
from diegosouzapw/awesome-omni-skill

Use when the user wants to log work items (bugs, features, tasks), track time spent, or view a daily/weekly work report.

asset-tracking

16
from diegosouzapw/awesome-omni-skill

Use when managing asset metadata, dependencies, and delivery workflows across teams.

analytics-metrics

16
from diegosouzapw/awesome-omni-skill

Build data visualization and analytics dashboards. Use when creating charts, KPI displays, metrics dashboards, or data visualization components. Triggers on analytics, dashboard, charts, metrics, KPI, data visualization, Recharts.

startup-metrics-framework

16
from diegosouzapw/awesome-omni-skill

This skill should be used when the user asks about \\\"key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests...

solo-founder-gtm

16
from diegosouzapw/awesome-omni-skill

When the user is a solo founder building their GTM motion, wants to scale without hiring, or needs to design an AI agent team for go-to-market. Also use when the user mentions 'solo founder,' 'one-person startup,' 'solopreneur,' 'bootstrapped,' 'no team,' 'AI agents as team,' 'scaling without hiring,' 'founder-led sales,' 'lean GTM,' 'one-person company,' or 'no employees.' This skill covers the complete solo founder GTM playbook from stack selection through agent team design, revenue-stage transitions, time allocation, and when to finally hire.

analytics-tracking

16
from diegosouzapw/awesome-omni-skill

(中文)When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," or "tracking plan." For A/B test measurement, see ab-test-setup.

prediction-tracking

16
from diegosouzapw/awesome-omni-skill

Track and evaluate AI predictions over time to assess accuracy. Use when reviewing past predictions to determine if they came true, failed, or remain uncertain.

analyzing-tdigest-metrics

16
from diegosouzapw/awesome-omni-skill

Analyze percentile metrics (tdigest type) using OPAL for latency analysis and SLO tracking. Use when calculating p50, p95, p99 from pre-aggregated duration or latency metrics. Covers the critical double-combine pattern with align + m_tdigest() + tdigest_combine + aggregate. For simple metrics (counts, averages), see aggregating-gauge-metrics skill.

alphaear-signal-tracker

16
from diegosouzapw/awesome-omni-skill

Track finance investment signal evolution and update logic based on new finance market information. Use when monitoring finance signals and determining if they are strengthened, weakened, or falsified.

aiwf:error-tracking

16
from diegosouzapw/awesome-omni-skill

Add Sentry v8 error tracking and performance monitoring to your project services. Use this skill when adding error handling, creating new controllers, instrumenting cron jobs, or tracking database performance. ALL ERRORS MUST BE CAPTURED TO SENTRY - no exceptions.

aggregating-performance-metrics

16
from diegosouzapw/awesome-omni-skill

Aggregate and centralize performance metrics from applications, systems, databases, caches, and services. Use when consolidating monitoring data from multiple sources. Trigger with phrases like "aggregate metrics", "centralize monitoring", or "collect performance data".