BC clean-csv-toolkit
Local CSV / TSV / JSONL inspection and cleanup toolkit. Profile, validate, deduplicate, diff, preview (head/tail/random sample), filter with a safe predicate language, sort, concat, merge (inner/left/right/outer joins), pivot (group-by aggregations + wide cross-tabs), transform (derived columns with safe expression evaluator: profit = revenue - cost, name = upper(first) + last, year(date), coalesce()), and convert between csv/tsv/jsonl/json/markdown. Pure Python 3 standard library, no pandas, no remote calls. Handles 100k+ rows in under 1 second.
As a process C 53/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 20. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Local CSV / TSV / JSONL inspection and cleanup toolkit. Profile, v… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 5500 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 53/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 11 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 5500 tokens
- 85Steps. 48 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- -32 of 17 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 552: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 48 items
- +3Output format is stated explicitly
- +4Has examples (19 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 53.