ToolMaster data-analysis
Analyze data sets, extract patterns, generate insights. Use when processing CSV/JSON data, building dashboards, market analysis, or making data-driven decisions.
install
source · Clone the upstream repo
git clone https://github.com/techieharry/ToolMaster
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/techieharry/ToolMaster "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data-analysis" ~/.claude/skills/techieharry-toolmaster-data-analysis && rm -rf "$T"
manifest:
skills/data-analysis/SKILL.mdsource content
Data Analysis
Process
- Understand the question — what decision does this analysis inform?
- Profile the data — shape, types, nulls, distributions, outliers
- Clean — handle missing values, normalize formats, remove duplicates
- Analyze — apply relevant techniques (aggregation, correlation, trends)
- Visualize — charts that answer the question (not decoration)
- Conclude — specific, actionable findings tied to the original question
Output structure
- Summary — 2-3 sentence answer to the question
- Key findings — bulleted, specific, with numbers
- Data quality notes — what was missing, what caveats apply
- Recommendations — what to do based on findings
Rules
- Always state sample size and time range
- Correlation is not causation — say "associated with" not "caused by"
- Include confidence level or margin of error when relevant
- If the data doesn't answer the question, say so