huashu-data-pro: From Excel to Insight-Ready Reports

Where this fits

A marketing manager drops a messy CSV export of last week's ad spend into chat and asks, "What happened, and what should we do next?" Without a structured skill, the agent flails: it might produce a vague summary, skip the ROI math, or generate a chart with a misleading Y-axis. huashu-data-pro gives agents a complete workflow—data cleaning, analysis, visualization, report writing, and even PPTX export—so they can move from raw data to a board-ready deliverable in one pass. It's for developers building agents that field data questions in Slack, email, or internal tools.

Why agents benefit

• Expert framing: The skill prompts the agent to adopt a specific role (analyst, optimization specialist) and ask clarifying questions before executing, reducing wrong-output risk.
• End-to-end delivery: Handles Excel parsing, ROI calculations, ECharts visualizations, HTML reports, and PPTX generation—so the agent doesn't have to stitch together multiple tools.
• Data honesty built in: Enforces zero-baseline charts, labeled sources, and refuses to fabricate numbers—critical for trust in automated reporting.
• Design system included: Predefined warm, professional visual style with SVG/inline JS (no CDN dependencies), so outputs are consistent and work offline in Playwright screenshots.
• "Think one step ahead": The skill instructs agents to proactively flag trends or anomalies the user didn't ask for—turning a task into insight.

Practical scenarios

Ad spend ROI post-mortem

A growth team asks for a weekly campaign review. The agent imports a CSV, calculates ROAS per channel, flags a drop in one campaign, and generates an interactive HTML report with a recommendation—all without being told to do the math.

Monthly business review deck

A finance manager needs a 10-slide PPTX for a leadership meeting. The agent pulls numbers from an Excel workbook, builds charts with proper scales, and exports a PPTX with a clean design—saving hours of manual formatting.

Exploratory data Q&A

A product manager asks, "Which features drive retention?" The agent explores the data, produces a terminal summary first, then offers a deeper HTML report with visualizations when the user wants more—matching output format to intent.

Add it to your agent workflow

Install the skill with:

npx skills add alchaincyf/huashu-skills --skill huashu-data-pro

Then in your agent prompt, trigger it naturally:

User: "Can you analyze this Excel file and give me a weekly report?"
Agent: (activates huashu-data-pro) "I'll start by cleaning the data and checking a few assumptions. What's your primary KPI—revenue or conversion rate?"

The skill will guide the agent through the full pipeline: parse → clean → analyze → visualize → report → export.

Compare before adopting

Before you wire this into production, compare three things:

• Quality signals: Check the skill's star count (1,390), recent commits, and whether the author responds to issues. Look at example outputs in the repo—do the charts and reports actually look good?
• Alternatives: Other data-analysis skills exist, but few cover the full workflow (Excel → report → PPTX). If you only need simple charting, a lighter skill might be enough.
• Workflow fit: Does the skill's output format (HTML report as default) match how your users consume results? If your agents are voice-only, you'll need to adapt.

Why it is worth tracking

huashu-data-pro is worth tracking because it addresses a real pain point—agents that can analyze data but can't present it professionally or honestly. The repository has 1,390 stars, indicating active community interest, and the skill's philosophy of "data honesty" and "think one step ahead" aligns with what enterprise users expect from AI assistants. Re-evaluate it when you're building reporting features, or when you need a reference for how to encode domain expertise into a skill. For a full breakdown, see the skill page at https://www.openagentskill.com/skills/alchaincyf-huashu-data-pro.