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database-scout

Explore SQLite and PostgreSQL databases: list tables, inspect schemas (columns/types/constraints), preview data, generate Mermaid ER diagrams, and run safe read-only queries. Triggered by requests to explore a database, view table structures, describe tables, generate diagrams, or query data, and by keywords like database exploration, schema, ER diagram, or SQL query.

70

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

82%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.

A well-organized, highly actionable body: every command is executable and verified against the bundled script, and there is no padding or condescension. The main improvement opportunities are removing the redundant Feature Overview table and moving the output examples to a reference file.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's knowledge (no explaining what databases or SQL are), but the Feature Overview table largely duplicates the Subcommands table and the opening line repeats the frontmatter description — minor trimming possible, matching the efficient-with-minor-overexplanation anchor.

4 / 5

Actionability

Every subcommand has a copy-paste-ready invocation for both SQLite and PostgreSQL, plus a parameter table and concrete output examples; the documented commands were verified against the actual argparse CLI in scripts/db_explorer.py.

5 / 5

Workflow Clarity

The skill is single-action per invocation and each command is unambiguous, so no multi-step sequence is needed and the read-only design avoids the destructive/batch validation cap; however, the body exceeds the simple-skill threshold and offers no guidance on handling failures (e.g., what the user sees when a query is blocked), leaving minor validation gaps.

4 / 5

Progressive Disclosure

Structure is good: a single real bundle script referenced consistently, clearly organized sections, no nested or buried references. The output-examples section (~50 lines of sample JSON/Mermaid) is inline content that could live in a reference file as the skill grows, keeping it below the ideal-split anchor.

4 / 5

Total

17

/

20

Passed

Description

88%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 description with concrete, third-person capability statements and an explicit trigger clause. Its only weaknesses are slightly incomplete synonym/extension coverage and mild overlap risk from the generic "SQL query" trigger.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "list tables, inspect schemas (columns/types/constraints), preview data, generate Mermaid ER diagrams, and run safe read-only queries" — with no vague filler, matching the comprehensive-coverage anchor.

5 / 5

Completeness

It explicitly answers both "what" (five concrete capabilities) and "when" ("Triggered by requests to explore a database, view table structures, describe tables, generate diagrams, or query data"), matching the anchor for a clearly explicit what-and-when pair.

5 / 5

Trigger Term Quality

Natural phrases like "explore a database", "view table structures", "describe tables", "ER diagram", and "SQL query" give good coverage, but common variations and file extensions (.db, .sqlite, "inspect database") are missing — fits the good-but-few-terms-missing anchor rather than comprehensive.

4 / 5

Distinctiveness Conflict Risk

The SQLite/PostgreSQL read-only exploration niche is clearly distinct with specific triggers, but generic terms like "SQL query" and "query data" carry minor overlap risk with general SQL-writing skills — the mostly-distinct-with-minor-overlap anchor.

4 / 5

Total

18

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
zebbern/claude-code-guide
Reviewed

Table of Contents

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