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csv-wrangling

Standard workflow order, tool selection matrix, and composition patterns for qsv CSV data wrangling

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./.claude/skills/skills/csv-wrangling/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is a lean, highly actionable reference with concrete command sequences, a clear workflow order that includes validation, and well-organized tables. Its main weaknesses are placeholder pipeline notation lacking full executable examples, a duplicated Parquet tip, and the absence of error-recovery feedback loops in the workflows.

Suggestions

Consolidate the duplicated Parquet advice (lines 67 and 112) into a single location to remove near-verbatim redundancy.

Provide one fully executable worked example with a real filename and complete command arguments (e.g., an actual sqlp TRIM/GROUP BY query) instead of 'sqlp (TRIM)' placeholders.

Add brief error-recovery guidance for key checkpoints, such as what to do when 'validate' fails against the JSON Schema or when sniff detects an unexpected delimiter.

DimensionReasoningScore

Conciseness

The body is dense, table-driven, and assumes Claude's competence with no padding or explanation of known concepts, but the Parquet-for-large-files advice appears nearly verbatim in two places ('For repeated SQL queries on large CSV (> 10MB), consider converting to Parquet' at lines 67 and 112), a minor trim opportunity that keeps it below anchor 5.

4 / 5

Actionability

Concrete commands and flags appear throughout ('stats --cardinality --stats-jsonl', 'select '!SSN'', 'blake3 --check checksums.b3'), but pipeline patterns use placeholder notation ('sqlp (TRIM)', 'sqlp (GROUP BY queries)') without full executable command syntax or a worked end-to-end example, fitting 'mostly executable with minor gaps'.

4 / 5

Workflow Clarity

The numbered 0-8 Standard Workflow Order is a clear sequence that includes an explicit validation stage (step 6 'Validate' with 'validate' and 'stats (verify results)', plus blake3 checksum verification), satisfying the validation requirement, but error-recovery feedback loops (validate -> fix -> retry) are absent, keeping it below anchor 5.

4 / 5

Progressive Disclosure

No bundle files exist, and the ~126-line body is well organized into clearly headed sections with appropriately sized inline reference tables, plus a 'Tool Discovery' pointer to the 57 remaining commands via mcp__qsv__qsv_search_tools; minor organization gaps (overlapping Operational Notes / Important Notes sections) fit anchor 4 rather than 5.

4 / 5

Total

16

/

20

Passed

Description

53%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description identifies a specific tool and domain and outlines the skill's contents, but it never states when the skill should be used and describes documentation structure rather than concrete capabilities. Adding a 'Use when...' trigger clause and naming the actual operations (clean, filter, join, aggregate, convert CSVs) would substantially improve it.

Suggestions

Add an explicit trigger clause, e.g. 'Use when processing, cleaning, or converting CSV/TSV files, or when the user mentions qsv, tabular data, or spreadsheet exports'.

Replace content-structure nouns ('tool selection matrix', 'composition patterns') with concrete capability verbs users would recognize — filter, dedupe, join, aggregate, validate, and convert CSV data.

Include file-format synonyms and extensions (TSV, .csv, tabular data) so the description matches natural user phrasing beyond the single keyword 'CSV'.

DimensionReasoningScore

Specificity

Names the domain ('qsv CSV data wrangling') and three concrete content items ('Standard workflow order, tool selection matrix, and composition patterns'), but these describe the skill's contents rather than concrete data actions like filter, join, or dedup, matching anchor 3 rather than the 'several specific actions' of anchor 4.

3 / 5

Completeness

The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines; it is not 2 because the 'what' is concrete and specific.

3 / 5

Trigger Term Quality

'CSV' and 'data wrangling' are natural user terms, but common variations and synonyms are missing — no TSV, tabular data, spreadsheet, or operation verbs (clean, dedupe, filter) — which fits 'some relevant keywords but missing common variations' rather than the fuller coverage of anchor 4.

3 / 5

Distinctiveness Conflict Risk

Naming the specific tool 'qsv' carves a clear niche with minimal conflict risk, but 'CSV data wrangling' could still overlap with generic data-analysis skills, so it falls just short of anchor 5's 'clear niche with distinct triggers'.

4 / 5

Total

13

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

dathere/qsv

Path

.claude/skills/skills/csv-wrangling/SKILL.md

Reviewed

Table of Contents

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