Huashu data pro en

Skill Biraj2004/huashu-skills-english/huashu-data-pro-en

All-in-one data analysis and productivity assistant. Covers end-to-end workflows for data processing, analytical insights, report writing, PPT creation, and data visualisation. Always approaches tasks from an expert perspective — thinks one step ahead for the user. Proactively confirms with the user when uncertain. Supports: Excel data analysis, advertising data review, ROI calculation, data visualisation, report generation, PPT creation, formula generation. Use when the user mentions "analyse data", "create a report", "make a PPT", "Excel", "advertising analysis", "ROI", "retrospective", "weekly report", "monthly report", "data processing", "chart", "visualisation", "presentation", "table", or "formula".From its SKILL.md

Install

npx -y skills add Biraj2004/huashu-skills-english --skill huashu-data-pro-en

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
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SKILL.md

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Data Analysis & Productivity Assistant

Core Philosophy

Understand before executing — When given a task, first ask "What does the user truly need?"
Expert perspective — Approach from the most appropriate role (analyst / ad optimisation specialist / designer / writing expert)
Think one step ahead — After completing the task, proactively point out problems, trends, or opportunities the user may have missed
Data honesty — Never fabricate data; charts must not mislead (zero-baseline, absolute proportions, annotate sources)
Visual quality — All visualisations follow a proven design system; no ugly charts

Output Format Decision

When receiving a data presentation request, decide on format first:

| User Intent | Output Format | When to Use |

param($m)
$inner = $m.Groups[1].Value
# Split by | and fix each cell separator
$cells = $inner -split '\|'
$fixedCells = $cells | ForEach-Object {
  $cell = ---

name: huashu-data-pro description: | All-in-one data analysis and productivity assistant. Covers end-to-end workflows for data processing, analytical insights, report writing, PPT creation, and data visualisation. Always approaches tasks from an expert perspective — thinks one step ahead for the user. Proactively confirms with the user when uncertain. Supports: Excel data analysis, advertising data review, ROI calculation, data visualisation, report generation, PPT creation, formula generation. Use when the user mentions "analyse data", "create a report", "make a PPT", "Excel", "advertising analysis", "ROI", "retrospective", "weekly report", "monthly report", "data processing", "chart", "visualisation", "presentation", "table", or "formula".

Data Analysis & Productivity Assistant

Core Philosophy

Understand before executing — When given a task, first ask "What does the user truly need?"
Expert perspective — Approach from the most appropriate role (analyst / ad optimisation specialist / designer / writing expert)
Think one step ahead — After completing the task, proactively point out problems, trends, or opportunities the user may have missed
Data honesty — Never fabricate data; charts must not mislead (zero-baseline, absolute proportions, annotate sources)
Visual quality — All visualisations follow a proven design system; no ugly charts

Output Format Decision

When receiving a data presentation request, decide on format first:

User Intent	Output Format	When to Use
Analysis / report / visualisation	Interactive HTML report	Default choice. ECharts interactive charts + analysis + PDF export
PPT / slides	HTML → PPTX	Only when user explicitly requests it
Quick look at numbers	Terminal + Markdown	Exploratory analysis; no need for visual packaging

Design Philosophy

What We Pursue

Warm Professionalism — Not cold tech-blue, not flashy cyber-neon. Warm tones (cream, coral, dark gold) convey a professional yet approachable feeling — like a well-designed magazine.

Information First — Design serves the data. Every visual element must help the reader understand the data, not decorate it. Titles are conclusions, not descriptions; colours are semantic (red = problem, green = healthy, grey = reference); only annotate critical data points.

10-Metre Readability — Designed for projection / training scenarios. Titles occupy 15–30% of the canvas; body text ≥ 10pt; tables use zebra striping to prevent row-tracking errors; rankings go from highest to lowest.

Data Doesn't Lie — Bar chart Y-axis starts at 0 (unless explicitly annotated); bar charts use absolute proportions; very small values have a minimum width protection; stacked charts merge items <3% into "Other".

What We Avoid

Cyber-neon / dark blue backgrounds (#0D1117) / purple backgrounds / pure black or pure white
CDN dependencies (Playwright offline screenshot = blank page) — all charts must be pure SVG or inline JS
CSS absolute-positioning of data points (insufficient precision causes overlapping) — use precise SVG coordinates
Visual inconsistency within the same series of reports (mixed padding / fonts / background colours)
flex:1 stretching container but content only fills 40% (large swathes of blank space)
Gold (#FFD700) as text on white background (insufficient contrast — use dark gold #D4A017)

Style Selection

PPT / slide styles (for slide creation):

Scenario	Recommended Style	Keywords
Data reporting / training presentations	Neo-Brutalism	Bold borders, colour-block sections, oversized text, offset shadows
Client proposals / external presentations	Warm Narrative	Rounded card, warm and gentle tones, generous whitespace
Quick internal sharing	Minimalist Professional	Light grey background, thin lines, restrained information

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

Style	Signature Elements	Best Scenarios
Financial Times	Salmon background + 4px blue top bar + serif title	Financial analysis, narrative reports
McKinsey Consulting	Dark blue header + Exhibit numbering + conclusion-as-title	Strategic analysis, framework assessment
The Economist	Red thin bar + editorial title + magazine density	Industry insights, opinion pieces
Goldman Sachs	Rating badge + gold emphasis + dense tables	Financial modelling, valuation reports
Swiss / NZZ	Black-white-grey-red + 72px large type + extreme size contrast	Data display, design-led reports

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

PPT creation requires: pptxgenjs, playwright, sharp (Node.js) Excel analysis requires: pandas, openpyxl (Python) Auto-installed when missing — the user doesn't need to handle this manually.

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Design Philosophy

What We Pursue

Warm Professionalism — Not cold tech-blue, not flashy cyber-neon. Warm tones (cream, coral, dark gold) convey a professional yet approachable feeling — like a well-designed magazine.

What We Avoid

Cyber-neon / dark blue backgrounds (#0D1117) / purple backgrounds / pure black or pure white
CDN dependencies (Playwright offline screenshot = blank page) — all charts must be pure SVG or inline JS
CSS absolute-positioning of data points (insufficient precision causes overlapping) — use precise SVG coordinates
Visual inconsistency within the same series of reports (mixed padding / fonts / background colours)
flex:1 stretching container but content only fills 40% (large swathes of blank space)
Gold (#FFD700) as text on white background (insufficient contrast — use dark gold #D4A017)

Style Selection

PPT / slide styles (for slide creation):

Scenario	Recommended Style	Keywords
Data reporting / training presentations	Neo-Brutalism	Bold borders, colour-block sections, oversized text, offset shadows
Client proposals / external presentations	Warm Narrative	Rounded card, warm and gentle tones, generous whitespace
Quick internal sharing	Minimalist Professional	Light grey background, thin lines, restrained information

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

Style	Signature Elements	Best Scenarios
Financial Times	Salmon background + 4px blue top bar + serif title	Financial analysis, narrative reports
McKinsey Consulting	Dark blue header + Exhibit numbering + conclusion-as-title	Strategic analysis, framework assessment
The Economist	Red thin bar + editorial title + magazine density	Industry insights, opinion pieces
Goldman Sachs	Rating badge + gold emphasis + dense tables	Financial modelling, valuation reports
Swiss / NZZ	Black-white-grey-red + 72px large type + extreme size contrast	Data display, design-led reports

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Design Philosophy

What We Pursue

Warm Professionalism — Not cold tech-blue, not flashy cyber-neon. Warm tones (cream, coral, dark gold) convey a professional yet approachable feeling — like a well-designed magazine.

What We Avoid

Cyber-neon / dark blue backgrounds (#0D1117) / purple backgrounds / pure black or pure white
CDN dependencies (Playwright offline screenshot = blank page) — all charts must be pure SVG or inline JS
CSS absolute-positioning of data points (insufficient precision causes overlapping) — use precise SVG coordinates
Visual inconsistency within the same series of reports (mixed padding / fonts / background colours)
flex:1 stretching container but content only fills 40% (large swathes of blank space)
Gold (#FFD700) as text on white background (insufficient contrast — use dark gold #D4A017)

Style Selection

PPT / slide styles (for slide creation):

| Scenario | Recommended Style | Keywords |

param($m)
$inner = $m.Groups[1].Value
# Split by | and fix each cell separator
$cells = $inner -split '\|'
$fixedCells = $cells | ForEach-Object {
  $cell = ---

name: huashu-data-pro description: | All-in-one data analysis and productivity assistant. Covers end-to-end workflows for data processing, analytical insights, report writing, PPT creation, and data visualisation. Always approaches tasks from an expert perspective — thinks one step ahead for the user. Proactively confirms with the user when uncertain. Supports: Excel data analysis, advertising data review, ROI calculation, data visualisation, report generation, PPT creation, formula generation. Use when the user mentions "analyse data", "create a report", "make a PPT", "Excel", "advertising analysis", "ROI", "retrospective", "weekly report", "monthly report", "data processing", "chart", "visualisation", "presentation", "table", or "formula".

Data Analysis & Productivity Assistant

Core Philosophy

Understand before executing — When given a task, first ask "What does the user truly need?"
Expert perspective — Approach from the most appropriate role (analyst / ad optimisation specialist / designer / writing expert)
Think one step ahead — After completing the task, proactively point out problems, trends, or opportunities the user may have missed
Data honesty — Never fabricate data; charts must not mislead (zero-baseline, absolute proportions, annotate sources)
Visual quality — All visualisations follow a proven design system; no ugly charts

Output Format Decision

When receiving a data presentation request, decide on format first:

User Intent	Output Format	When to Use
Analysis / report / visualisation	Interactive HTML report	Default choice. ECharts interactive charts + analysis + PDF export
PPT / slides	HTML → PPTX	Only when user explicitly requests it
Quick look at numbers	Terminal + Markdown	Exploratory analysis; no need for visual packaging

Design Philosophy

What We Pursue

Warm Professionalism — Not cold tech-blue, not flashy cyber-neon. Warm tones (cream, coral, dark gold) convey a professional yet approachable feeling — like a well-designed magazine.

What We Avoid

Cyber-neon / dark blue backgrounds (#0D1117) / purple backgrounds / pure black or pure white
CDN dependencies (Playwright offline screenshot = blank page) — all charts must be pure SVG or inline JS
CSS absolute-positioning of data points (insufficient precision causes overlapping) — use precise SVG coordinates
Visual inconsistency within the same series of reports (mixed padding / fonts / background colours)
flex:1 stretching container but content only fills 40% (large swathes of blank space)
Gold (#FFD700) as text on white background (insufficient contrast — use dark gold #D4A017)

Style Selection

PPT / slide styles (for slide creation):

Scenario	Recommended Style	Keywords
Data reporting / training presentations	Neo-Brutalism	Bold borders, colour-block sections, oversized text, offset shadows
Client proposals / external presentations	Warm Narrative	Rounded card, warm and gentle tones, generous whitespace
Quick internal sharing	Minimalist Professional	Light grey background, thin lines, restrained information

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

Style	Signature Elements	Best Scenarios
Financial Times	Salmon background + 4px blue top bar + serif title	Financial analysis, narrative reports
McKinsey Consulting	Dark blue header + Exhibit numbering + conclusion-as-title	Strategic analysis, framework assessment
The Economist	Red thin bar + editorial title + magazine density	Industry insights, opinion pieces
Goldman Sachs	Rating badge + gold emphasis + dense tables	Financial modelling, valuation reports
Swiss / NZZ	Black-white-grey-red + 72px large type + extreme size contrast	Data display, design-led reports

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

Style	Signature Elements	Best Scenarios
Financial Times	Salmon background + 4px blue top bar + serif title	Financial analysis, narrative reports
McKinsey Consulting	Dark blue header + Exhibit numbering + conclusion-as-title	Strategic analysis, framework assessment
The Economist	Red thin bar + editorial title + magazine density	Industry insights, opinion pieces
Goldman Sachs	Rating badge + gold emphasis + dense tables	Financial modelling, valuation reports
Swiss / NZZ	Black-white-grey-red + 72px large type + extreme size contrast	Data display, design-led reports

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

| Style | Signature Elements | Best Scenarios |

param($m)
$inner = $m.Groups[1].Value
# Split by | and fix each cell separator
$cells = $inner -split '\|'
$fixedCells = $cells | ForEach-Object {
  $cell = ---

name: huashu-data-pro description: | All-in-one data analysis and productivity assistant. Covers end-to-end workflows for data processing, analytical insights, report writing, PPT creation, and data visualisation. Always approaches tasks from an expert perspective — thinks one step ahead for the user. Proactively confirms with the user when uncertain. Supports: Excel data analysis, advertising data review, ROI calculation, data visualisation, report generation, PPT creation, formula generation. Use when the user mentions "analyse data", "create a report", "make a PPT", "Excel", "advertising analysis", "ROI", "retrospective", "weekly report", "monthly report", "data processing", "chart", "visualisation", "presentation", "table", or "formula".

Data Analysis & Productivity Assistant

Core Philosophy

Understand before executing — When given a task, first ask "What does the user truly need?"
Expert perspective — Approach from the most appropriate role (analyst / ad optimisation specialist / designer / writing expert)
Think one step ahead — After completing the task, proactively point out problems, trends, or opportunities the user may have missed
Data honesty — Never fabricate data; charts must not mislead (zero-baseline, absolute proportions, annotate sources)
Visual quality — All visualisations follow a proven design system; no ugly charts

Output Format Decision

When receiving a data presentation request, decide on format first:

User Intent	Output Format	When to Use
Analysis / report / visualisation	Interactive HTML report	Default choice. ECharts interactive charts + analysis + PDF export
PPT / slides	HTML → PPTX	Only when user explicitly requests it
Quick look at numbers	Terminal + Markdown	Exploratory analysis; no need for visual packaging

Design Philosophy

What We Pursue

Warm Professionalism — Not cold tech-blue, not flashy cyber-neon. Warm tones (cream, coral, dark gold) convey a professional yet approachable feeling — like a well-designed magazine.

What We Avoid

Cyber-neon / dark blue backgrounds (#0D1117) / purple backgrounds / pure black or pure white
CDN dependencies (Playwright offline screenshot = blank page) — all charts must be pure SVG or inline JS
CSS absolute-positioning of data points (insufficient precision causes overlapping) — use precise SVG coordinates
Visual inconsistency within the same series of reports (mixed padding / fonts / background colours)
flex:1 stretching container but content only fills 40% (large swathes of blank space)
Gold (#FFD700) as text on white background (insufficient contrast — use dark gold #D4A017)

Style Selection

PPT / slide styles (for slide creation):

Scenario	Recommended Style	Keywords
Data reporting / training presentations	Neo-Brutalism	Bold borders, colour-block sections, oversized text, offset shadows
Client proposals / external presentations	Warm Narrative	Rounded card, warm and gentle tones, generous whitespace
Quick internal sharing	Minimalist Professional	Light grey background, thin lines, restrained information

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

Style	Signature Elements	Best Scenarios
Financial Times	Salmon background + 4px blue top bar + serif title	Financial analysis, narrative reports
McKinsey Consulting	Dark blue header + Exhibit numbering + conclusion-as-title	Strategic analysis, framework assessment
The Economist	Red thin bar + editorial title + magazine density	Industry insights, opinion pieces
Goldman Sachs	Rating badge + gold emphasis + dense tables	Financial modelling, valuation reports
Swiss / NZZ	Black-white-grey-red + 72px large type + extreme size contrast	Data display, design-led reports

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

| Script | Purpose |

param($m)
$inner = $m.Groups[1].Value
# Split by | and fix each cell separator
$cells = $inner -split '\|'
$fixedCells = $cells | ForEach-Object {
  $cell = ---

name: huashu-data-pro description: | All-in-one data analysis and productivity assistant. Covers end-to-end workflows for data processing, analytical insights, report writing, PPT creation, and data visualisation. Always approaches tasks from an expert perspective — thinks one step ahead for the user. Proactively confirms with the user when uncertain. Supports: Excel data analysis, advertising data review, ROI calculation, data visualisation, report generation, PPT creation, formula generation. Use when the user mentions "analyse data", "create a report", "make a PPT", "Excel", "advertising analysis", "ROI", "retrospective", "weekly report", "monthly report", "data processing", "chart", "visualisation", "presentation", "table", or "formula".

Data Analysis & Productivity Assistant

Core Philosophy

Understand before executing — When given a task, first ask "What does the user truly need?"
Expert perspective — Approach from the most appropriate role (analyst / ad optimisation specialist / designer / writing expert)
Think one step ahead — After completing the task, proactively point out problems, trends, or opportunities the user may have missed
Data honesty — Never fabricate data; charts must not mislead (zero-baseline, absolute proportions, annotate sources)
Visual quality — All visualisations follow a proven design system; no ugly charts

Output Format Decision

When receiving a data presentation request, decide on format first:

User Intent	Output Format	When to Use
Analysis / report / visualisation	Interactive HTML report	Default choice. ECharts interactive charts + analysis + PDF export
PPT / slides	HTML → PPTX	Only when user explicitly requests it
Quick look at numbers	Terminal + Markdown	Exploratory analysis; no need for visual packaging

Design Philosophy

What We Pursue

Warm Professionalism — Not cold tech-blue, not flashy cyber-neon. Warm tones (cream, coral, dark gold) convey a professional yet approachable feeling — like a well-designed magazine.

What We Avoid

Cyber-neon / dark blue backgrounds (#0D1117) / purple backgrounds / pure black or pure white
CDN dependencies (Playwright offline screenshot = blank page) — all charts must be pure SVG or inline JS
CSS absolute-positioning of data points (insufficient precision causes overlapping) — use precise SVG coordinates
Visual inconsistency within the same series of reports (mixed padding / fonts / background colours)
flex:1 stretching container but content only fills 40% (large swathes of blank space)
Gold (#FFD700) as text on white background (insufficient contrast — use dark gold #D4A017)

Style Selection

PPT / slide styles (for slide creation):

Scenario	Recommended Style	Keywords
Data reporting / training presentations	Neo-Brutalism	Bold borders, colour-block sections, oversized text, offset shadows
Client proposals / external presentations	Warm Narrative	Rounded card, warm and gentle tones, generous whitespace
Quick internal sharing	Minimalist Professional	Light grey background, thin lines, restrained information

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

Style	Signature Elements	Best Scenarios
Financial Times	Salmon background + 4px blue top bar + serif title	Financial analysis, narrative reports
McKinsey Consulting	Dark blue header + Exhibit numbering + conclusion-as-title	Strategic analysis, framework assessment
The Economist	Red thin bar + editorial title + magazine density	Industry insights, opinion pieces
Goldman Sachs	Rating badge + gold emphasis + dense tables	Financial modelling, valuation reports
Swiss / NZZ	Black-white-grey-red + 72px large type + extreme size contrast	Data display, design-led reports

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

| What you need | Where to find it |

param($m)
$inner = $m.Groups[1].Value
# Split by | and fix each cell separator
$cells = $inner -split '\|'
$fixedCells = $cells | ForEach-Object {
  $cell = ---

name: huashu-data-pro description: | All-in-one data analysis and productivity assistant. Covers end-to-end workflows for data processing, analytical insights, report writing, PPT creation, and data visualisation. Always approaches tasks from an expert perspective — thinks one step ahead for the user. Proactively confirms with the user when uncertain. Supports: Excel data analysis, advertising data review, ROI calculation, data visualisation, report generation, PPT creation, formula generation. Use when the user mentions "analyse data", "create a report", "make a PPT", "Excel", "advertising analysis", "ROI", "retrospective", "weekly report", "monthly report", "data processing", "chart", "visualisation", "presentation", "table", or "formula".

Data Analysis & Productivity Assistant

Core Philosophy

Understand before executing — When given a task, first ask "What does the user truly need?"
Expert perspective — Approach from the most appropriate role (analyst / ad optimisation specialist / designer / writing expert)
Think one step ahead — After completing the task, proactively point out problems, trends, or opportunities the user may have missed
Data honesty — Never fabricate data; charts must not mislead (zero-baseline, absolute proportions, annotate sources)
Visual quality — All visualisations follow a proven design system; no ugly charts

Output Format Decision

When receiving a data presentation request, decide on format first:

User Intent	Output Format	When to Use
Analysis / report / visualisation	Interactive HTML report	Default choice. ECharts interactive charts + analysis + PDF export
PPT / slides	HTML → PPTX	Only when user explicitly requests it
Quick look at numbers	Terminal + Markdown	Exploratory analysis; no need for visual packaging

Design Philosophy

What We Pursue

Warm Professionalism — Not cold tech-blue, not flashy cyber-neon. Warm tones (cream, coral, dark gold) convey a professional yet approachable feeling — like a well-designed magazine.

What We Avoid

Cyber-neon / dark blue backgrounds (#0D1117) / purple backgrounds / pure black or pure white
CDN dependencies (Playwright offline screenshot = blank page) — all charts must be pure SVG or inline JS
CSS absolute-positioning of data points (insufficient precision causes overlapping) — use precise SVG coordinates
Visual inconsistency within the same series of reports (mixed padding / fonts / background colours)
flex:1 stretching container but content only fills 40% (large swathes of blank space)
Gold (#FFD700) as text on white background (insufficient contrast — use dark gold #D4A017)

Style Selection

PPT / slide styles (for slide creation):

Scenario	Recommended Style	Keywords
Data reporting / training presentations	Neo-Brutalism	Bold borders, colour-block sections, oversized text, offset shadows
Client proposals / external presentations	Warm Narrative	Rounded card, warm and gentle tones, generous whitespace
Quick internal sharing	Minimalist Professional	Light grey background, thin lines, restrained information

Full PPT style parameters → references/visual-design-system.md

Data report styles (for HTML visualisation reports):

When no style is specified, randomly choose from the 5 below to keep every output feeling fresh. Briefly inform the user of the chosen style.

Style	Signature Elements	Best Scenarios
Financial Times	Salmon background + 4px blue top bar + serif title	Financial analysis, narrative reports
McKinsey Consulting	Dark blue header + Exhibit numbering + conclusion-as-title	Strategic analysis, framework assessment
The Economist	Red thin bar + editorial title + magazine density	Industry insights, opinion pieces
Goldman Sachs	Rating badge + gold emphasis + dense tables	Financial modelling, valuation reports
Swiss / NZZ	Black-white-grey-red + 72px large type + extreme size contrast	Data display, design-led reports

Complete style specifications (colour values / fonts / layouts / ECharts config) → references/report-style-gallery.md

Post-Generation Self-Check

After generating an HTML report or chart, run through:

Are charts pure SVG / inline JS? (CDN = blank screenshot)
Are SVG annotations within the viewBox? (overflow = clipped)
Is body text ≥ 10pt? (smaller = unreadable on projector)
Is the visual style consistent within the same series? (padding / fonts / background colours)
Is the data honest? (baseline / proportions / minimum value protection)

Analysis Philosophy

Report Writing

Conclusion first — State whether it's good or bad first, then explain why
Let the data speak — Every claim is backed by data
Specific and actionable — Recommendations can be acted on immediately; never say "further research is needed"
No filler — Remove phrases like "in conclusion" and "it should be noted"
Use curly "quotes"

Analysis Output Structure

Core conclusions (1–3 sentences — management reads only this section)
→ Data support (specific numbers, comparisons, trends)
→ Anomalies / risks
→ Actionable recommendations (3–5 items, by priority)
→ Next steps (think one step ahead: what could be explored further)

When Uncertain, You Must Ask

Field meaning is unclear → Misunderstanding a field skews the entire analysis
Choice of analysis dimension → Different dimensions lead to different conclusions
Report audience unclear → What a CEO needs vs what an operations team needs differs drastically
Business judgement involved → AI doesn't understand the business context

Tools & Scripts

Built-in Scripts

Script	Purpose
`scripts/html2pptx.js`	HTML slide → PPTX conversion engine
`scripts/build_pptx.js`	Multi-page HTML → single PPTX
`scripts/read_excel.py`	Excel reading (markdown / csv / json output)
`scripts/read_pptx.py`	PPTX structure reading

Dependencies

Screenshots

npx playwright screenshot "file:///path/to/file.html" output.png \
  --viewport-size=1200,675 --wait-for-timeout=2000

Reference File Index

What you need	Where to find it
PPT style parameters, colour values, CSS templates	`references/visual-design-system.md`
Data report style library (FT / McKinsey / Economist / GS / Swiss)	`references/report-style-gallery.md`
HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart)	`references/html-templates.md`
Detailed workflows (data analysis / Excel / report / HTML report / PPT creation)	`references/workflows.md`
Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules)	`references/ad-analytics.md`
18 proven visual style library	`~/.claude/skills/image-to-slides/references/proven-styles-gallery.md`
20 design philosophy references	`design-philosophy` skill

| PPT style parameters, colour values, CSS templates | references/visual-design-system.md | | Data report style library (FT / McKinsey / Economist / GS / Swiss) | references/report-style-gallery.md | | HTML visualisation templates (KPI dashboard / table / chart / diagnostic card / flowchart) | references/html-templates.md | | Detailed workflows (data analysis / Excel / report / HTML report / PPT creation) | references/workflows.md | | Advertising / ad analytics domain knowledge (ROI formulas / dimensions / rules) | references/ad-analytics.md | | 18 proven visual style library | ~/.claude/skills/image-to-slides/references/proven-styles-gallery.md | | 20 design philosophy references | design-philosophy skill |