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How this skill is triggered — by the user, by Claude, or both
Slash command
/hatch3r:hatch3r-cli-millerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
<!-- HATCH3R-CLI-SKILL-GENERATED v1 -->
Parse, transform, clean, and analyze CSV files: auto-detect formats, filter/sort/merge/pivot, generate stats/outliers, with Python (pandas) and JavaScript examples.
Guides qsv-based CSV wrangling with standard workflow order, tool selection matrix for tasks like filtering/joining/aggregating, selection syntax, and pipeline patterns for cleaning/profiling.
Share bugs, ideas, or general feedback.
awk/sed/cut/join for CSV/TSV/JSON/Parquet streams
Reach for mlr when the task is in the data category and the agent would otherwise call an MCP tool or read large outputs into context.
CLI tools return structured stdout that fits in <1KB for typical queries; equivalent MCP calls regularly exceed 10KB. Reference: Anthropic engineering (Nov 4 2025) — code-execution-over-MCP yields 98.7% token reduction.
mlr --c2t cat data.csv
Convert CSV to TSV on stdout — handy for piping into shell tools that prefer tab delimiters.
mlr --csv stats1 -a mean,stddev -f price products.csv
Compute mean and stddev of the price column.
mlr --icsv --ojson put '$tax = $amount * 0.07' transactions.csv
Read CSV, add a computed column, emit JSON — chained format conversion plus DSL transform.
mlr --csv filter '$status == "active"' users.csv
Row filter using the put/filter DSL — operates on streams of arbitrary size.
mlr --csv join -j id -f orders.csv customers.csv
SQL-style join on id between two CSVs, streamed.
hatch3r-cli-duckdb (tier 2) has a query planner and parallel scan; mlr is streaming-single-thread.hatch3r-cli-qsv (tier 2) is faster for trivial slicing.| Tool | When to prefer |
|---|---|
hatch3r-cli-duckdb (tier 2) | Multi-GB data, joins, analytical SQL, Parquet |
hatch3r-cli-qsv (tier 2) | Single-column slice, count, sample on plain CSV |
hatch3r-cli-csvkit (tier 3) | SQL-over-CSV with csvsql, Python integration |
Verify with:
command -v mlr
Install (mac):
# brew
brew install miller
Homepage: https://miller.readthedocs.io/