Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add rockyflux/yq-workflow --skill sql-code-reviewgit clone --depth 1 https://github.com/rockyflux/yq-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rockyflux/yq-workflow/sql-code-review)<a href="https://agentmods.dev/skills/rockyflux/yq-workflow/sql-code-review"><img src="https://agentmods.dev/badge/skills/rockyflux/yq-workflow/sql-code-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rockyflux/yq-workflow/sql-code-review"><img src="https://agentmods.dev/badge/skills/rockyflux/yq-workflow/sql-code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.02140 |
| Opus 5.5 | $0.00026 | $0.00856 |
| Sonnet 5.5 | $0.00013 | $0.00428 |
| Haiku 4.5 | $0.00006 | $0.00214 |
Grade A, and why
sql-code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to sql-code-review — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQL Code Review
Perform a thorough SQL code review of ${selection} (or entire project if no selection) focusing on security, performance, maintainability, and database best practices.
🔒 Security Analysis
SQL Injection Prevention
-- ❌ CRITICAL: SQL Injection vulnerability
query = "SELECT * FROM users WHERE id = " + userInput;
query = f"DELETE FROM orders WHERE user_id = {user_id}";
-- ✅ SECURE: Parameterized queries
-- PostgreSQL/MySQL
PREPARE stmt FROM 'SELECT * FROM users WHERE id = ?';
EXECUTE stmt USING @user_id;
-- SQL Server
EXEC sp_executesql N'SELECT * FROM users WHERE id = @id', N'@id INT', @id = @user_id;
Access Control & Permissions
- Principle of Least Privilege: Grant minimum required permissions
- Role-Based Access: Use database roles instead of direct user permissions
- Schema Security: Proper schema ownership and access controls
- Function/Procedure Security: Review DEFINER vs INVOKER rights
Data Protection
- Sensitive Data Exposure: Avoid SELECT * on tables with sensitive columns
- Audit Logging: Ensure sensitive operations are logged
- Data Masking: Use views or functions to mask sensitive data
- Encryption: Verify encrypted storage for sensitive data
⚡ Performance Optimization
Query Structure Analysis
-- ❌ BAD: Inefficient query patterns
SELECT DISTINCT u.*
FROM users u, orders o, products p
WHERE u.id = o.user_id
AND o.product_id = p.id
AND YEAR(o.order_date) = 2024;
-- ✅ GOOD: Optimized structure
SELECT u.id, u.name, u.email
FROM users u
INNER JOIN orders o ON u.id = o.user_id
WHERE o.order_date >= '2024-01-01'
AND o.order_date < '2025-01-01';
Index Strategy Review
- Missing Indexes: Identify columns that need indexing
- Over-Indexing: Find unused or redundant indexes
- Composite Indexes: Multi-column indexes for complex queries
- Index Maintenance: Check for fragmented or outdated indexes
Join Optimization
- Join Types: Verify appropriate join types (INNER vs LEFT vs EXISTS)
- Join Order: Optimize for smaller result sets first
- Cartesian Products: Identify and fix missing join conditions
- Subquery vs JOIN: Choose the most efficient approach
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 302 lines · 65 tokens per session scan A 2e67c2fa2875
sql-code-review is a skill published in the GitHub repository rockyflux/yq-workflow (2 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 2,140 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to sql-code-review, differing in 4 lines, and is treated as a copy.
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