data-quality-checker
Data Quality Checker - Auto-activating skill for Data Pipelines. Triggers on: data quality checker, data quality checker Part of the Data Pipelines skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill data-quality-checkerOverall
score
17%
Does it follow best practices?
Validation for skill structure
Activation
0%This description is essentially a placeholder with no substantive content. It fails on all dimensions by only stating the skill name and category without describing capabilities, use cases, or meaningful trigger terms. The duplicate trigger term suggests this may be auto-generated boilerplate that was never properly filled in.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Validates data schemas, detects null values, identifies outliers, checks referential integrity, and reports data anomalies in pipeline outputs.'
Add a 'Use when...' clause with natural trigger terms like 'validate data', 'check data quality', 'find data errors', 'data validation', 'null checks', 'data integrity', or 'anomaly detection'.
Specify the data formats or contexts this skill handles (e.g., 'CSV files', 'database tables', 'JSON payloads', 'ETL pipelines') to distinguish it from other data-related skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the skill ('Data Quality Checker') without describing any concrete actions. There are no specific capabilities listed like 'validates schemas', 'detects anomalies', or 'checks for null values'. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and provides no explicit 'when to use' guidance. The 'Triggers on' section just repeats the skill name rather than describing actual use cases. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated twice ('data quality checker, data quality checker'). No natural user keywords like 'validate data', 'check for nulls', 'data validation', 'anomaly detection', or 'data integrity' are included. | 1 / 3 |
Distinctiveness Conflict Risk | The description is extremely generic - 'Data Pipelines' and 'Data Quality Checker' could overlap with many data-related skills. No specific file types, data formats, or unique capabilities are mentioned to distinguish it. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
0%This skill is an empty template with no substantive content. It describes capabilities in abstract marketing language but provides zero actionable guidance, code examples, or concrete instructions for data quality checking. The content would be useless to Claude attempting to perform actual data quality tasks.
Suggestions
Add concrete, executable code examples for common data quality checks (null detection, schema validation, duplicate detection, outlier identification)
Define a clear workflow with validation steps: e.g., 1) Profile data, 2) Define quality rules, 3) Run checks, 4) Review failures, 5) Remediate or flag
Include specific tool guidance (e.g., Great Expectations, dbt tests, custom Spark validations) with copy-paste ready configurations
Remove all generic filler text ('provides automated assistance', 'follows best practices') and replace with actual techniques and patterns
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic filler text that explains nothing Claude doesn't already know. Phrases like 'provides automated assistance' and 'follows industry best practices' are meaningless without specifics. | 1 / 3 |
Actionability | No concrete code, commands, or executable guidance provided. The entire skill describes what it does abstractly without showing how to actually perform data quality checks. | 1 / 3 |
Workflow Clarity | No workflow steps, validation checkpoints, or process sequences are defined. The skill mentions 'step-by-step guidance' but provides none. | 1 / 3 |
Progressive Disclosure | No references to detailed documentation, no structured navigation, and no separation of content. The skill is a shallow placeholder with no depth to disclose. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
69%Validation — 11 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 11 / 16 Passed | |
- Reviewed
Table of Contents
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