sql-pro
Optimize SQL With Expert Database Guidance
Complex SQL work can slow teams when schemas, indexes, and workloads are unclear. This skill guides query tuning, schema design, and cloud database decisions.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "sql-pro" from https://skillstore.io/skills/sickn33-sql-pro.md and its manifest at https://skillstore.io/api/skills/sickn33-sql-pro/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "sql-pro". A dashboard query scans a large orders table and times out during business hours.
Expected outcome:
- Identifies full-table scans, missing selective indexes, and aggregation pressure as likely causes.
- Recommends reviewing execution plans, adding a targeted composite index, and testing on a read replica.
Using "sql-pro". A SaaS team needs a multi-tenant database model with compliance controls.
Expected outcome:
- Compares shared-table, schema-per-tenant, and database-per-tenant designs.
- Highlights tenant isolation, backup scope, row-level security, and operational cost tradeoffs.
Using "sql-pro". A team plans to move analytics from a legacy warehouse to a cloud platform.
Expected outcome:
- Outlines migration phases for discovery, data validation, workload testing, and cutover.
- Calls out cost controls, partition strategy, access controls, and rollback planning.
Security Audit
SafeAll six static system-reconnaissance hits are false positives caused by database-domain wording in SKILL.md. The file gives query optimization, schema design, and production safety guidance. No prompt injection, network access, or executable code was found.
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APA citation
sickn33. (2026). sql-pro security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-sql-pro/audits/5BibTeX citation
@techreport{sickn33-sickn33-sql-pro-2026,
author = {sickn33},
title = {sql-pro security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-sql-pro/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "sql-pro security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-07"
url: "https://skillstore.io/skills/sickn33-sql-pro/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-sql-pro:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Tune Slow Reporting Queries
Analyze execution plans, table sizes, and indexes to reduce latency in dashboards and reports.
Design Application Schemas
Create practical table models, constraints, indexes, and tenant patterns for transactional applications.
Plan Cloud Database Changes
Compare database platforms, migration options, replication patterns, and cost controls for growing systems.
Try These Prompts
Review this slow SQL query and explain likely bottlenecks. Ask for missing schema or plan details before recommending changes.
Design a reporting schema for these business metrics, source tables, freshness needs, and expected query patterns.
Evaluate this analytical workload across table sizes, partitions, indexes, and execution plans. Recommend safe tuning steps.
Create a migration plan from this current database to a cloud-native SQL platform. Include risks, validation, rollback, and performance checks.
Best Practices
- Provide table sizes, indexes, query plans, and database engine versions with each request.
- Test tuning recommendations in staging before applying them to production.
- Include workload goals, latency targets, and data growth assumptions.
Avoid
- Asking for optimization without schema, indexes, or execution plans.
- Running exploratory analysis directly on production without limits or read replicas.
- Copying database-specific advice across engines without compatibility checks.