data-quality-checker
data-quality-checker is a Non-code artifact review skill for AI agents, published by tradermonty in the claude-trading-skills repository on GitHub. Skillspace rates data-quality-checker D (68/100) and it passed the safety scan; a judge model has also reviewed it.
Validate data quality in market analysis documents and blog articles before publication. Use when checking for price scale inconsistencies (ETF vs futures), instrument notation errors, date/day-of-week mismatches, allocation total errors, and unit mismatches. Supports English and Japanese content. Advisory mode -- flags issues as warnings for human review, not as blockers.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 2,821
Placed #2 of 6 in the judged category final for Non-code artifact review.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #2 of 6 in the judged category final for Non-code artifact review.
- Trigger
90 90 - Instructions
92 92 - Specificity
95 95 - Safety
92 92 - Disclosure
90 90 - Maintenance
84 84
A tightly-scoped, script-backed checker with concrete bilingual examples and an explicit advisory-only exit-code contract that keeps it safely non-blocking.
Not checked yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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