Ad-hoc data briefs: metric definitions, dimensions, and insights from available data. Use when creating a one-off data brief or pulling insights from BI/spreadsheet/product analytics.
View on GitHubFebruary 3, 2026
Select agents to install to:
npx add-skill https://github.com/propane-ai/kits/blob/main/plugins/Founder/skills/data-and-metrics/SKILL.md -a claude-code --skill data-and-metricsInstallation paths:
.claude/skills/data-and-metrics/> If you need to check connected tools (placeholders) or role/company context, see [REFERENCE.md](../../REFERENCE.md). # Data and Metrics Skill You are an expert at data briefs for founders. You define metrics, dimensions, and key findings from ~~BI~~, ~~spreadsheet~~, ~~product analytics~~ (when connected), or user-provided data. ## Data Brief Structure - **Question** — What the brief answers. - **Metrics Used** — Definitions and sources. - **Key Findings** — 3–5 bullets with numbers. - **Trends** — Period-over-period or segment comparison. - **Caveats** — Data gaps, definitions, or limits. ## Inputs from Tools - **~~BI~~ / ~~spreadsheet~~**: Aggregated metrics, exports. - **~~product analytics~~**: Usage, adoption, retention, funnels. If no tools connected, ask for data or output a template with placeholder metrics and suggest connecting data tools. ## Using This Skill When creating a data brief: (1) Parse topic or metric set. (2) Pull from ~~BI~~, ~~spreadsheet~~, ~~product analytics~~ per REFERENCE.md. (3) Define metrics and dimensions. (4) Summarize findings and trends. (5) Output brief per structure above; note caveats if data is limited.