data-quality-frameworks

Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

Quality

78%

Does it follow best practices?

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/data-quality-frameworks/SKILL.md

The canonical home for this skill is data-quality-frameworks in rmyndharis/antigravity-skills

Quality

Content

68%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 body is well-organized and token-efficient but leans too heavily on abstract instructions and a missing reference file. It lacks executable specifics and validation checkpoints for a workflow that automates batch data validation.

Suggestions

Add concrete executable guidance in the Instructions, e.g. a sample Great Expectations expectation_suite snippet, a dbt test YAML block, or a data-contract schema template, rather than only abstract bullets.

Insert explicit validation/verification checkpoints into the workflow (run tests -> review failures -> fix -> re-run) before the 'Automate validation in CI/CD' step.

Create the referenced resources/implementation-playbook.md (currently absent) so the deferred detailed frameworks, templates, and examples actually resolve.

Dimension	Reasoning	Score
Conciseness	Lean and efficient with no padding or explanation of concepts Claude already knows; every section earns its place and it assumes Claude's competence.	5 / 5
Actionability	Names concrete frameworks and gives a sequenced set of actions, but the Instructions are high-level hints ("Define expectations/tests and contract rules") with no executable code, commands, or templates, deferring all specifics to the referenced playbook.	3 / 5
Workflow Clarity	Steps are listed in a rough sequence (identify -> define -> automate -> alert/remediate) but there are no explicit validation or verification checkpoints; for a CI/CD batch-validation workflow this caps clarity at 3 per the rubric.	3 / 5
Progressive Disclosure	Good section structure with a clearly signaled one-level-deep reference ("open resources/implementation-playbook.md"), but the referenced file does not exist in the bundle, so the deferred navigation is partially broken and keeps it from a 5.	4 / 5
	Total	15 / 20 Passed

Description

87%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.

A strong, well-structured description that clearly states capabilities and trigger conditions using third-person voice and concrete tool names. It is concise, explicit, and highly distinguishable from sibling skills.

Dimension	Reasoning	Score
Specificity	Names the domain plus concrete tools ("Great Expectations, dbt tests, and data contracts") and a concrete action ("Implement data quality validation"), but coverage of actions is narrow rather than comprehensive.	4 / 5
Completeness	Explicitly answers both what ("Implement data quality validation with Great Expectations, dbt tests, and data contracts") and when ("Use when building data quality pipelines, implementing validation rules, or establishing data contracts") with concrete trigger phrases.	5 / 5
Trigger Term Quality	Includes natural phrases a user would say ("building data quality pipelines", "implementing validation rules", "establishing data contracts") plus named frameworks, though a few common synonyms are missing.	4 / 5
Distinctiveness Conflict Risk	A clear niche anchored to specific frameworks (Great Expectations, dbt tests, data contracts) with distinct triggers, giving minimal overlap risk with other skills.	5 / 5
	Total	18 / 20 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: plugins/AI-Agents-Safe-Coding-Skills-claude/skills/data-quality-frameworks/SKILL.md
Commit: 57c135b

Reviewed: 3 days ago

Table of Contents

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