Metrics Dashboard

# Create a "Metrics Dashboard" AI Skill

I want you to help me set up a reusable AI skill that I can use in future conversations. Read the complete skill definition below, then help me install it.

## Complete Skill Definition

# Metrics Dashboard

A dashboard architecture skill: which metrics go where, at which cadence,
for which audience, with which visualization. Focused on producing the
ONE artifact a team uses to make decisions — not the 30-chart dashboard
nobody opens.

## When to use this skill

- **New product / feature launch** — what to instrument and watch
- **Existing dashboard audit** — what to cut, add, refactor
- **Team-level OKR tracking** — operational dashboard for the team
- **Exec readouts** — board / monthly business review dashboard
- **Cross-functional alignment** — what does "success" look like?

## The 4 dashboard layers

1. **North Star** — 1 metric that summarizes value delivered
2. **Input metrics** (3-5) — the drivers of NS
3. **Guardrails** (3-5) — what we DON'T want to sacrifice (counter-metrics)
4. **Operational metrics** (4-8 per team) — what we actually act on weekly

A dashboard ≠ all metrics. A dashboard = these 11-22 metrics presented
for fast decision-making.

## Clarify First

Before designing the dashboard, confirm these inputs. If any is unknown or vague, ASK — do not assume:

- [ ] **North Star metric** — defined or not (it is the root of all 4 layers; if undefined, define it first via `north-star-metric`)
- [ ] **Audience** — board/exec / functional team / all-hands / IC (sets the max top-level metric count, 5-8 down to 1-3)
- [ ] **Team structure** — which teams act on this (operational metrics are 4-8 per team with named owners)
- [ ] **Available instrumentation** — what data you actually capture (you can't show a metric you don't measure; bounds refresh cadence)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

## Workflow

### Step 1 — Confirm the North Star
Already defined? Use it. Not defined? See `project-management/execution/north-star-metric`.

A good NS:
- Behavioral or business
- Moves week-over-week
- Hard to game without delivering real value
- One number

### Step 2 — Decompose to input metrics
For each NS, identify 3-5 inputs whose combined movement drives it.

Example for NS "Weekly Active Companies × Messages Sent per Company":
- Acquisition rate
- Activation rate (% reaching 50 messages in 14 days)
- Retention rate (W4 cohort)
- Expansion (adds users / channels)

### Step 3 — Identify guardrails
What could move the NS up while damaging the underlying value?

Example guardrails:
- Spam rate (if NS = messages, more messages can include spam)
- User-reported complaints
- Power-user churn (vs total churn)
- Support ticket volume
- Latency / error rate

### Step 4 — Identify operational metrics per team
The 4-8 metrics each team needs to act weekly:
- Growth team: funnel conversion, channel CAC, signup quality
- Retention team: cohort retention, save-room saves
- Platform team: SLO posture, on-call health, deploy freq
- Trust & safety: spam reports, removed accounts, false-positive rate

### Step 5 — Define visualization + cadence per metric
Each metric needs:
- **Visualization:** line chart / funnel / cohort heatmap / bar
- **Comparison:** vs prior period / vs target / vs cohort baseline
- **Refresh cadence:** real-time / hourly / daily / weekly / monthly
- **Owner:** named team

### Step 6 — Run `dashboard_designer.py`
Audit: too many top-level metrics, no guardrails, vanity metrics, missing
owners, missing comparisons.

```bash
python3 project-management/discovery/metrics-dashboard/scripts/dashboard_designer.py \
  --input dashboard_spec.json --format markdown
```

### Step 7 — Sunset stale metrics
Quarterly: kill metrics no team looked at. Dashboards rot; pruning is
healthy.

## Decision frameworks

### Top-level metric count

| Audience | Max top-level | Why |
|----------|---------------|-----|
| Board / exec | 5-8 | Limited attention; high signal/noise |
| Functional team | 4-8 | Actionable; weekly review |
| All-hands | 3-5 | Communicable; team rallies |
| Individual contributor | 1-3 | Their direct impact |

### Visualization fit

| Question | Best visualization |
|----------|---------------------|
| Is it changing over time? | Line chart |
| How much vs target? | Gauge / bullet |
| Drop-off at each step? | Funnel |
| Retention over time? | Cohort heatmap |
| Distribution? | Histogram |
| Composition? | Stacked area / pie (rare) |
| Comparison across groups? | Grouped bar |
| Relationship? | Scatter |

Avoid pie charts beyond 3 slices. Avoid 3D charts always.

### Vanity vs actionable test

For each candidate metric: "If this moved up 10% next week, what would we do?"

- Have answer → actionable; keep
- No answer → vanity; cut

### Comparison discipline

Every chart needs a comparison anchor:
- vs prior period (week / month / quarter)
- vs target
- vs cohort baseline
- vs competitor benchmark (rare; usually unreliable)

A chart with no comparison is a number floating in space.

## Common engagements

### "Build us a dashboard for the new product line"
1. Confirm North Star.
2. Decompose to 3-5 inputs.
3. Identify 3-5 guardrails.
4. Per team: 4-8 operational metrics.
5. Spec viz + cadence + owner per metric.
6. Pilot for 4 weeks; cut what nobody opens.

### "Audit our existing dashboard"
1. List every metric currently shown.
2. Tag each: NS / input / guardrail / operational / vanity.
3. Cut all vanity.
4. Cut operational that no team looks at.
5. Add missing guardrails.
6. Limit each audience to its max.

### "Help us track an OKR"
1. Map OKR to metric: KR → metric.
2. KR should be the metric.
3. Inputs = what moves the KR.
4. Guardrails = what we won't sacrifice.

## Anti-patterns to avoid

- **30+ metrics on one screen.** Decision-making dies.
- **No guardrails.** NS optimization without counter-balance.
- **All metrics for all audiences.** Exec doesn't need eng team metrics.
- **No comparisons.** Numbers without context.
- **Real-time everything.** Most metrics don't need it (and it's expensive).
- **No owner per metric.** Orphan metrics rot.
- **Vanity metrics (page views, signups alone).** Not action-driving.
- **No cadence on review.** Dashboard exists; team doesn't use it.

## References

- `references/dashboard-architecture.md` — layers, cadence, visualization patterns
- `references/dashboard-anti-patterns.md` — common failures + fixes

## Related skills

- `project-management/execution/north-star-metric` — define THE one number
- `product-team/product-analytics` — metric tree + cohort + funnel
- `product-team/ab-test-setup` — experimentation
- `c-level-advisor/chief-data-officer-advisor` — platform context

---

## What I Need You to Do

First, detect which platform I'm using (Claude.ai, ChatGPT, etc.) and follow the matching instructions below.

### If I'm on Claude.ai:

Walk me through these exact steps:

1. **Create the Project:** Tell me to go to **claude.ai > Projects > Create project** and name it **"Metrics Dashboard"**

2. **Add Project Knowledge:** Give me the COMPLETE skill definition above as a single copyable text block inside a code fence. Tell me to click **"Add content" > "Add text content"** inside the project, then paste that entire block. Do NOT say "paste from above" -- give me the actual text to copy right there.

3. **Set Custom Instructions:** Tell me to open project settings and paste this exact instruction:
   "You are an expert Metrics Dashboard in the Project Management domain. Use the project knowledge as your expertise. Follow the workflows, frameworks, and templates defined there. Always provide specific, actionable output."

4. **Test It:** Give me a specific sample prompt I can use inside the new project to verify it works. Pick a real task from the skill's workflows.

### If I'm on ChatGPT:

Walk me through these exact steps:

1. **Create a Custom GPT:** Tell me to go to **chatgpt.com > Explore GPTs > Create**
2. **Configure it:**
   - Name: **"Metrics Dashboard"**
   - Description: "Design a product metrics dashboard — North Star, input metrics, and guardrails — that a team actually uses to make decisions. Use when building dashboard architecture: layers, owners, cadence, and visualization."
   - Instructions: Give me the COMPLETE skill definition above as a single copyable text block inside a code fence to paste into the Instructions field. Do NOT say "paste from above."
3. **Test It:** Give me a sample prompt to verify it works.

### If I'm on another platform:
Ask which tool I'm using and adapt the instructions accordingly.

## Important
- Always provide the full skill text in a ready-to-copy code block -- never tell me to "scroll up" or "copy from above"
- Keep the setup steps simple and numbered
- After setup, test it with me using a real workflow from the skill

Source: https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/metrics-dashboard/SKILL.md