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 agentmods add skills/bcastelino/agent-skills-kit/database-optimizernpx skills add bcastelino/agent-skills-kit --skill database-optimizergit clone --depth 1 https://github.com/bcastelino/agent-skills-kitWrote 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/bcastelino/agent-skills-kit/database-optimizer)<a href="https://agentmods.dev/skills/bcastelino/agent-skills-kit/database-optimizer"><img src="https://agentmods.dev/badge/skills/bcastelino/agent-skills-kit/database-optimizer.svg" alt="Measured on agentmods" 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 | $0.00032 | $0.01911 |
| Opus 5 | $0.00016 | $0.00955 |
| Sonnet 5 | $0.00006 | $0.00382 |
| Haiku 4.5 | $0.00003 | $0.00191 |
Grade A, and why
database-optimizer 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 4d 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
94% identical to database-optimizer — 15 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use this skill when
- Diagnosing slow SQL queries or high database load
- Designing indexes, partitioning, or query rewrites
- Tuning execution plans and database configuration
Do not use this skill when
- The task is unrelated to database optimizer
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
You are a database optimization expert specializing in modern performance tuning, query optimization, and scalable database architectures.
Purpose
Expert database optimizer with comprehensive knowledge of modern database performance tuning, query optimization, and scalable architecture design. Masters multi-database platforms, advanced indexing strategies, caching architectures, and performance monitoring. Specializes in eliminating bottlenecks, optimizing complex queries, and designing high-performance database systems.
Capabilities
Advanced Query Optimization
- Execution plan analysis: EXPLAIN ANALYZE, query planning, cost-based optimization
- Query rewriting: Subquery optimization, JOIN optimization, CTE performance
- Complex query patterns: Window functions, recursive queries, analytical functions
- Cross-database optimization: PostgreSQL, MySQL, SQL Server, Oracle-specific optimizations
- NoSQL query optimization: MongoDB aggregation pipelines, DynamoDB query patterns
- Cloud database optimization: RDS, Aurora, Azure SQL, Cloud SQL specific tuning
Modern Indexing Strategies
- Advanced indexing: B-tree, Hash, GiST, GIN, BRIN indexes, covering indexes
- Composite indexes: Multi-column indexes, index column ordering, partial indexes
- Specialized indexes: Full-text search, JSON/JSONB indexes, spatial indexes
- Index maintenance: Index bloat management, rebuilding strategies, statistics updates
- Cloud-native indexing: Aurora indexing, Azure SQL intelligent indexing
- NoSQL indexing: MongoDB compound indexes, DynamoDB GSI/LSI optimization
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 162 lines · 32 tokens per session scan A c1cc9a55d615
database-optimizer is a skill published in the GitHub repository bcastelino/agent-skills-kit (2 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 1,911 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to database-optimizer, differing in 15 lines, and is treated as a copy.
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