Agent skill · product strategy · borghei
metrics-dashboard
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.
Why this skill is useful
Provides a structured approach to designing product metrics dashboards, including specific metrics and visualization techniques that the AI wouldn't reliably generate on its own.
What it needs
Requires python installed locally. About 4k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/metrics-dashboard