This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks to "optimize SQL queries", "explore database schemas", "generate migration SQL", "analyze query performance", or "document database structure".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Category: Engineering Domain: Database Development & Optimization
The SQL Database Assistant skill provides tools for analyzing SQL query performance, exploring database schemas from DDL files, and generating migration SQL from schema differences. It helps teams write efficient queries, maintain clean schemas, and manage database evolution safely.
Before analyzing or generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
# Analyze a SQL query for performance issues
python scripts/query_optimizer.py --file slow_query.sql
# Analyze inline SQL
python scripts/query_optimizer.py --query "SELECT * FROM users WHERE name LIKE '%john%'"
# Explore schema from DDL file
python scripts/schema_explorer.py --file schema.sql
# Generate migration from schema diff
python scripts/migration_generator.py --from old_schema.sql --to new_schema.sql
# JSON output
python scripts/query_optimizer.py --file query.sql --format json
Analyzes SQL queries for performance issues and optimization opportunities.
| Feature | Description |
|---|---|
| SELECT * detection | Flags queries selecting all columns |
| Missing index hints | Identifies WHERE/JOIN columns likely needing indexes |
| N+1 detection | Flags correlated subquery patterns |
| Full table scan | Detects queries without WHERE clauses on large tables |
| JOIN analysis | Checks join conditions and types |
| LIKE optimization | Flags leading wildcard LIKE patterns |
Generates documentation from SQL DDL (CREATE TABLE) files.
| Feature | Description |
|---|---|
| Table catalog | Lists all tables with column counts |
| Column details | Documents types, nullability, defaults |
| Index listing | Catalogs indexes and their columns |
| Relationship mapping | Identifies foreign key relationships |
| Markdown output | Generates schema documentation |
Generates migration SQL by comparing two schema DDL files.
| Feature | Description |
|---|---|
| Column additions | ALTER TABLE ADD COLUMN for new columns |
| Column removals | ALTER TABLE DROP COLUMN for removed columns |
| Type changes | ALTER TABLE ALTER COLUMN for type modifications |
| New tables | CREATE TABLE for entirely new tables |
| Dropped tables | DROP TABLE for removed tables |
| Index changes | CREATE/DROP INDEX for index differences |
# Lint SQL queries
python scripts/query_optimizer.py --file queries/ --format json --strict
# Generate schema docs
python scripts/schema_explorer.py --file schema.sql --format markdown > SCHEMA.md
| Pattern | Issue | Fix |
|---|---|---|
SELECT * | Fetches unnecessary data | List specific columns |
LIKE '%term%' | Cannot use index | Use full-text search |
| Correlated subquery | N+1 query pattern | Rewrite as JOIN |
| No WHERE clause | Full table scan | Add filtering conditions |
OR in WHERE | Poor index usage | Use UNION or IN |
| Functions on indexed columns | Prevents index use | Apply to value side |
| Query Pattern | Index Type |
|---|---|
WHERE col = value | B-tree on col |
WHERE col1 = v AND col2 = v | Composite (col1, col2) |
ORDER BY col | B-tree on col |
WHERE col LIKE 'prefix%' | B-tree on col |
WHERE col IN (...) | B-tree on col |
| Full-text search | Full-text index |
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This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.