Skip to content
Get packs

Data Analytics Bundle

Guides an agent through data quality checks, KPI work, dashboards, reports and market sizing

Source Download skill
Repository
XiaomiMiMo/MiMo-Code
Stars
13,743
Licence
MIT
Files
15 files

What it does

This skill gives the agent a structured playbook for quantitative product and business analysis. It is an entry point that routes a request to the most relevant focused workflow, such as checking data quality, diagnosing a metric change, designing KPIs, building a dashboard or report, or sizing a market. The agent then follows that workflow's steps and keeps source notes and uncertainty visible in its results. Output is kept portable: Markdown, a self-contained HTML file, a notebook, a spreadsheet, or a static chart image.

Great for

  • Product or business analysts who want consistent, evidence-backed analysis from an AI agent
  • Teams producing recurring KPI reports or simple dashboards without a BI tool
  • Developers who want reproducible Python or Matplotlib charts and notebooks from an agent

Skip it if

  • Decisions with legal, medical or financial consequences made on the agent's output alone, since the skill does not verify source data
  • Users who expect live connections to warehouses or Google Workspace out of the box; those depend on whatever tools the host environment provides and the skill does not supply them
  • Anyone needing React or interactive frontend dashboards, which the bundle explicitly excludes

Try asking

  • “Check this sales CSV for data quality problems before I trust the numbers”
  • “Diagnose why our weekly active users dropped 12% last month”
  • “Design a KPI set for our new subscription onboarding flow”
  • “Build a self-contained HTML dashboard summarising churn by cohort”
Step-by-step guide: how to use Data Analytics BundleInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 15 original files, the MIT licence and an attribution note.

    data-analytics.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip data-analytics.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip data-analytics.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Point the agent at real data files or a connected source; ask it to state which source each number came from
  • Name the output you want (Markdown, HTML, notebook, spreadsheet) so the agent produces a durable file rather than only a chat answer
  • Review the data-quality section of any analysis before acting on conclusions

What's inside

  • SKILL.md
  • workflows/analyze-data-quality/SKILL.md
  • workflows/build-dashboard/SKILL.md
  • workflows/build-report/report-to-google-doc/SKILL.md
  • workflows/build-report/report-to-google-slides/SKILL.md
  • workflows/build-report/report-to-pdf/SKILL.md
  • workflows/build-report/SKILL.md
  • workflows/create-data-context/SKILL.md
  • workflows/design-kpis/SKILL.md
  • workflows/gather-business-context/SKILL.md
  • workflows/index/SKILL.md
  • workflows/jupyter-notebooks/SKILL.md
  • workflows/kpi-reporting/SKILL.md
  • workflows/market-sizing/SKILL.md
  • workflows/metric-diagnostics/SKILL.md

Redistributed unmodified from XiaomiMiMo/MiMo-Code under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.