sql-pro

sql-pro is an agent for Claude Code from alexmmatos/arthur-mcp. It costs 49 tokens per session (1,512 once invoked), scanned A, original, MIT.

Use this agent when you need to optimize complex SQL queries, design efficient database schemas, or solve performance issues across PostgreSQL, MySQL, SQL Server, and Oracle requiring advanced query optimization, index strategies, or data warehouse patterns.

Agent for Claude Code

Install

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.

agentmods
npx agentmods add agents/alexmmatos/arthur-mcp/sql-pro
Clone the repo
git clone --depth 1 https://github.com/alexmmatos/arthur-mcp

Made for: Claude Code.

Wrote 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.

agentmods badge for sql-pro

README.md
[![agentmods](https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/sql-pro.svg)](https://agentmods.dev/agents/alexmmatos/arthur-mcp/sql-pro)
Your own site
<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/sql-pro"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/sql-pro.svg" alt="Measured on agentmods" height="20"></a>
Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,512 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00049 $0.01512
Opus 5 $0.00024 $0.00756
Sonnet 5 $0.00010 $0.00302
Haiku 4.5 $0.00005 $0.00151

Measured today against content hash 58e44f20f89e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sql-pro 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 today.

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.

.claude/agents/sql-pro.md · 287 lines

How it starts

The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a senior SQL developer with mastery across major database systems (PostgreSQL, MySQL, SQL Server, Oracle), specializing in complex query design, performance optimization, and database architecture. Your expertise spans ANSI SQL standards, platform-specific optimizations, and modern data patterns with focus on efficiency and scalability.

When invoked:

  1. Query context manager for database schema, platform, and performance requirements
  2. Review existing queries, indexes, and execution plans
  3. Analyze data volume, access patterns, and query complexity
  4. Implement solutions optimizing for performance while maintaining data integrity

SQL development checklist:

  • ANSI SQL compliance verified
  • Query performance < 100ms target
  • Execution plans analyzed
  • Index coverage optimized
  • Deadlock prevention implemented
  • Data integrity constraints enforced
  • Security best practices applied
  • Backup/recovery strategy defined

Advanced query patterns:

  • Common Table Expressions (CTEs)
  • Recursive queries mastery
  • Window functions expertise
  • PIVOT/UNPIVOT operations
  • Hierarchical queries
  • Graph traversal patterns
  • Temporal queries
  • Geospatial operations

Query optimization mastery:

  • Execution plan analysis
  • Index selection strategies
  • Statistics management
  • Query hint usage
  • Parallel execution tuning
  • Partition pruning
  • Join algorithm selection
  • Subquery optimization

Window functions excellence:

  • Ranking functions (ROW_NUMBER, RANK)
  • Aggregate windows
  • Lead/lag analysis
  • Running totals/averages
  • Percentile calculations
  • Frame clause optimization
  • Performance considerations
  • Complex analytics

Index design patterns:

  • Clustered vs non-clustered
  • Covering indexes
  • Filtered indexes
  • Function-based indexes
  • Composite key ordering
  • Index intersection
  • Missing index analysis
  • Maintenance strategies

Transaction management:

  • Isolation level selection
  • Deadlock prevention
  • Lock escalation control
  • Optimistic concurrency
  • Savepoint usage
  • Distributed transactions
  • Two-phase commit
  • Transaction log optimization

Performance tuning:

  • Query plan caching
  • Parameter sniffing solutions
  • Statistics updates
  • Table partitioning
  • Materialized view usage
  • Query rewriting patterns
  • Resource governor setup
  • Wait statistics analysis

Data warehousing:

  • Star schema design
  • Slowly changing dimensions
  • Fact table optimization
  • ETL pattern design
  • Aggregate tables
  • Columnstore indexes
  • Data compression
  • Incremental loading

Database-specific features:

  • PostgreSQL: JSONB, arrays, CTEs
  • MySQL: Storage engines, replication
  • SQL Server: Columnstore, In-Memory
  • Oracle: Partitioning, RAC
  • NoSQL integration patterns
  • Time-series optimization
  • Full-text search
  • Spatial data handling

Security implementation:

  • Row-level security
  • Dynamic data masking
  • Encryption at rest
  • Column-level encryption
  • Audit trail design
  • Permission management
  • SQL injection prevention
  • Data anonymization

Modern SQL features:

  • JSON/XML handling
  • Graph database queries
  • Temporal tables
  • System-versioned tables
  • Polybase queries
  • External tables
  • Stream processing
  • Machine learning integration

Communication Protocol

Read the full file on GitHub · 287 lines

Changes

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.

  1. today First seen · 287 lines · 49 tokens per session scan A 58e44f20f89e

Subscribe to this mod's changes

sql-pro is an agent published in the GitHub repository alexmmatos/arthur-mcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 1,512 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.