csv-wrangling
Standard workflow order, tool selection matrix, and composition patterns for qsv CSV data wrangling
Skill by Kilo-Org
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/kilo-org-csv-wrangling
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About
Use cases: spreadsheets, data, productivity
Reviews
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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
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Files it touches
~/.claude/skills/csv-wrangling
What's inside
- Skill name
csv-wrangling- Description
- Standard workflow order, tool selection matrix, and composition patterns for qsv CSV data wrangling
- License
- Apache-2.0
- Metadata
- category: data
- Instructions
- 122 lines in SKILL.md · view on GitHub
Files (2)
- LICENSE
- SKILL.md
SKILL.md (first lines)
# CSV Wrangling with qsv ## Standard Workflow Order Always follow this sequence when processing CSV data: 0. **Setup (Cowork)** - If relative paths don't resolve, call `mcp__qsv__qsv_get_working_dir` and `mcp__qsv__qsv_set_working_dir` to sync 1. **Index** - `index` (enables fast random access for subsequent commands) 2. **Discover** - `sniff` (detect format, encoding, delimiter) -> `headers` -> `count` 3. **Profile** - `stats --cardinality --stats-jsonl` (creates cache used by smart commands) 4. **Inspect** - `slice --len 5` (preview rows), `frequency --frequency-jsonl` (value distributions with cache for reuse) 5. **Transform** - select, sort, dedup, rename, replace, search, sqlp, etc. 6. **Validate** - `validate` (against JSON Schema), `stats` (verify results) 7. **Export** - `tojsonl`, `table`, `mcp__qsv__qsv_to_parquet`, `to` (xlsx/sqlite/postgres/ods/datapackage) 8. **Document** - `describegpt --all` (AI-generated Data Dictionary, Description & Tags) ## Tool Selection Matrix | Task | Best Tool | Alternative | When to Use Alternative | |------|-----------|-------------|------------------------| | Select columns | `select` | `sqlp` | Need computed columns | | Filter rows | `search` | `sqlp` | Complex WHERE conditions | | Sort data | `sort` | `sqlp` | Need ORDER BY with LIMIT | | Remove duplicates | `dedup` | `sqlp` | Need GROUP BY dedup | | Join two files | `joinp` | `join` | `join` for memory-constrained | | Aggregate/GROUP BY | `sqlp` | `frequency` | `frequency` for simple counts; `--frequency-jsonl` creates cache | | Column stats | `stats` | `moarstats` | `moarstats` for extended stats | | Find/replace | `replace` | `sqlp` | `sqlp` for conditional replace | | Reshape wide->long | `transpose --long` | - | DuckDB UNPIVOT (external) for complex reshaping | | Reshape long->wide | `pivotp` | `sqlp` | Complex pivots | | Concatenate files | `cat rows` | `cat rowskey` | Different column orders | | Sample rows | `sample` | `slice` | `slice` for positional ranges | | Document dataset | `describegpt` | — | AI-generated Data Dictionary, Description & Tags | ## qsv Selection Syntax Used by `select`, `search`, `sort`, `dedup`, `frequency`, and other commands: | Syntax | Meaning | Example | |--------|---------|---------| | `name` | Column by name | `select "City"` | | `1` | Column by 1-based index | `select 1` | | `1,3,5` | Multiple columns | `select 1,3,5` | | `1-5` | Range (inclusive) | `select 1-5` | | `!col` | Exclude column | `select '!SSN'` | | `!1-3` | Exclude range | `select '!1-3'` | | `/regex/` | Match column names | `select '/^price/'` | ## Common Pipeline Patterns ### Clean and Deduplicate ``` sniff -> index -> safenames -> fixlengths -> sqlp (TRIM) -> dedup -> validate ``` ### Profile and Analyze ``` sniff -> index -> stats --cardinality --stats-jsonl -> read .stats.csv -> frequency (on key columns) -> sqlp (GROUP BY queries) ``` **Before writing SQL**: read `.stats.csv` to learn column types, cardinality, nullcount, min/max, sort order. Run `frequency` on columns you'll GROUP BY or filter on. Use this to write precise WHERE clauses, correct type casts, and avoid unnecessary COALESCE. For repeated SQL queries on large CSV (> 10MB), consider converting to Parquet: `sniff -> index -> stats -> to_parquet -> sqlp (using read_parquet())`. Note: `sqlp` can query CSV of any size directly. ### Join and Enrich ``` index (both files) -> stats (both) -> joinp -> select (keep needed columns) -> sort ``` ### Profile and Document ``` sniff -> index -> stats --cardinality --stats-jsonl -> describegpt --all ``` ### Convert and Export ``` excel (to CSV) -> index -> stats -> select -> tojsonl / qsv_to_parquet ``` ### Batch Convert to Multiple Formats ``` excel (to CSV) -> index -> stats -> to xlsx report.xlsx excel (to CSV) -> index -> stats -> to sqlite report.db excel (to CSV) -> index -> stats -> to parquet parquet_output_dir ``` ### File Integrity Verification ``` blake3 file.csv > checksums.b3 (before transfer) -> blake3 --check checksums.b3 (after transfer) ``` ## Delimiter Handling - CSV (`,`): default, no flag needed - TSV (`\t`): use `--delimiter '\t'` or file extension `.tsv` - SSV (`;`): use `--delimiter ';'` or file extension `.ssv` - Auto-detect: set `QSV_SNIFF_DELIMITER=1` environment variable ## Important Notes - Column indices are **1-based**, not 0-based - `--no-headers` flag changes behavior significantly - most commands assume headers exist - Output goes to stdout by default; use `--output file.csv` to write to file - Many commands auto-detect `.sz` (Snappy compressed) files transparently - `cat rows` requires same column order; use `cat rowskey` for different schemas - `dedup` loads all data into memory and sorts internally; use `--sorted` flag if input is already sorted to enable streaming mode with constant memory - `sort` loads entire file into memory; for huge files use `sqlp` with ORDER BY - For repeated SQL queries on large CSV (> 10MB), consider converting to Parquet with `mcp__qsv__qsv_to_parquet` for faster performance. Parquet works ONLY with `sqlp` and DuckDB — all other qsv commands need CSV/TSV/SSV input ## Tool Discovery Use **`mcp__qsv__qsv_search_tools`** to discover commands beyond the initially loaded core tools. There are 55 qsv skill-based commands covering selection, filtering, transformation, aggregation, joining, validation, formatting, conversion, and more. ## Operational Notes - **Timeout**: Default operation timeout is 10 minutes (configurable via `QSV_MCP_OPERATION_TIMEOUT_MS`, max 30 min). Allow operations to run to completion. - **Memory**: `dedup`, `sort`, `reverse`, `table`, `transpose`, `pragmastat`, and `stats` (with extended stats) load entire files into memory. For files >1GB, prefer `extdedup`/`extsort` via `mcp__qsv__qsv_command`. - **Cowork path architecture**: qsv runs on the HOST machine. File paths must be valid on the host. Always verify with `mcp__qsv__qsv_get_working_dir`. - **Sequential operations**: Prefer sequential over parallel qsv calls to avoid queuing delays: index → stats → analysis. - **Large files (>5GB)**: Let `mcp__qsv__qsv_frequency` run to completion. Only fall back to `mcp__qsv__qsv_sqlp` with GROUP BY if the server timeout is exceeded.
From Kilo-Org/kilo-marketplace, Apache-2.0.
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Signals
- Stars
- 195
- Forks
- 328
- Open issues
- 18
- Last commit (this folder)
- Jun 24, 2026 (4 months ago)
- Last release
- Sep 28, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/Kilo-Org/kilo-marketplace
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
csv-wrangling skill. Agent Mart. https://agentmart.dev/skills/kilo-org-csv-wrangling (last updated 2026-10-24)