generating-database-seed-data

Process this skill enables AI assistant to generate realistic test data and database seed scripts for development and testing environments. it uses faker libraries to create realistic data, maintains relational integrity, and allows configurable data volumes. u... Use when working with databases or data models. Trigger with phrases like 'database', 'query', or 'schema'.

Quality

77%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

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tessl review fix ./plugins/database/data-seeder-generator/skills/generating-database-seed-data/SKILL.md

Quality

Content

62%Weight 40%Scale 1-3

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 well-structured, actionable guide with a clear validated workflow, but it stays monolithic rather than offloading detail into the (currently empty) bundle files, and its examples are fragments rather than fully runnable scripts.

Suggestions

Populate the placeholder bundle files (e.g. scripts/seed_database.py, scripts/validate_seed_data.py, assets/example_seed_script.sql) and link to them from the body so progressive disclosure is real rather than promised.

Provide at least one complete, runnable example seed script in assets/ rather than only illustrative SQL fragments in step 7.

Trim the Examples section to one concise worked example and move the others into a references/ file, reducing token cost while preserving coverage.

Dimension	Reasoning	Score
Conciseness	The body mostly assumes Claude's competence — no padding explaining what databases or Faker are — but the three lengthy Examples paragraphs and the full Prerequisites list add volume that could be trimmed without losing clarity.	2 / 3
Actionability	Concrete faker API calls and output-format snippets are given, but they are illustrative fragments rather than a complete, copy-paste-runnable end-to-end seed script, leaving the guidance actionable but incomplete.	2 / 3
Workflow Clarity	A clearly sequenced 10-step process culminates in an explicit validation step (step 10) checking foreign keys, uniques, check constraints, and row counts, and the Error Handling table provides feedback-loop guidance for a batch database operation.	3 / 3
Progressive Disclosure	The SKILL.md is well-sectioned but effectively monolithic: the references/, scripts/, and assets/ bundles contain only placeholder READMEs with unchecked intended files that do not exist, and the body never links to any of them.	2 / 3
	Total	9 / 12 Passed

Description

92%Weight 40%Scale 1-3

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 is strong: it covers concrete capabilities, natural trigger terms, and an explicit 'what + when' structure. Its main weakness is that the trigger terms are generic enough to risk overlap with sibling database skills, and the prose has a garbled opening ('Process this skill enables...') and a stray 'u...' artifact.

Suggestions

Tighten the opening to clean, third-person imperative prose (e.g., 'Generates realistic test data and database seed scripts...') and remove the truncated 'u...' artifact.

Add a more distinctive trigger term such as 'seed', 'fixtures', or 'test data' to reduce overlap with general database/migration skills.

Drop the meta phrasing 'Process this skill enables AI assistant to...' which is redundant with the skill being invoked by an AI assistant.

Dimension	Reasoning	Score
Specificity	The description names multiple concrete actions — 'generate realistic test data and database seed scripts', 'maintains relational integrity', 'allows configurable data volumes' — matching the anchor for listing several specific concrete actions.	3 / 3
Completeness	It explicitly states what the skill does (generate seed data, maintain integrity, configurable volumes) and when to use it ('Use when working with databases or data models. Trigger with phrases like...'), satisfying both halves with explicit triggers.	3 / 3
Trigger Term Quality	'database', 'query', and 'schema' are natural terms a user would say, and they are framed with an explicit 'Use when... Trigger with phrases like...' clause, giving good coverage of relevant trigger terms.	3 / 3
Distinctiveness Conflict Risk	The triggers 'database', 'query', and 'schema' are broad and could overlap with general database or migration skills, even though seed-data generation is itself a niche; it is somewhat specific but not clearly conflict-free.	2 / 3
	Total	11 / 12 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Path: plugins/database/data-seeder-generator/skills/generating-database-seed-data/SKILL.md
Commit: c4eafaf

Reviewed: 5 days ago

Table of Contents

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