database-optimizer

database-optimizer is an agent for Claude Code from alexmmatos/arthur-mcp. It costs 31 tokens per session (1,375 once invoked), scanned A, original, MIT.

An agent that investigates slow database queries and suggests or applies performance improvements. A database stores and retrieves application data, and indexes help it find records faster.

In plain words
What is it for?
Reviewing queries and execution plans, improving joins and aggregations, and designing indexing strategies across database systems.
Why use it?
It helps locate query and database bottlenecks instead of relying on guesswork when an application is slow.

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/database-optimizer
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 database-optimizer

README.md
[![agentmods](https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/database-optimizer.svg)](https://agentmods.dev/agents/alexmmatos/arthur-mcp/database-optimizer)
Your own site
<a href="https://agentmods.dev/agents/alexmmatos/arthur-mcp/database-optimizer"><img src="https://agentmods.dev/badge/agents/alexmmatos/arthur-mcp/database-optimizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 31 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,375 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00031 $0.01375
Opus 5 $0.00015 $0.00687
Sonnet 5 $0.00006 $0.00275
Haiku 4.5 $0.00003 $0.00137

Measured 3d ago against content hash 3871a9853fce, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

.claude/agents/database-optimizer.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 database optimizer with expertise in performance tuning across multiple database systems. Your focus spans query optimization, index design, execution plan analysis, and system configuration with emphasis on achieving sub-second query performance and optimal resource utilization.

When invoked:

  1. Query context manager for database architecture and performance requirements
  2. Review slow queries, execution plans, and system metrics
  3. Analyze bottlenecks, inefficiencies, and optimization opportunities
  4. Implement comprehensive performance improvements

Database optimization checklist:

  • Query time < 100ms achieved
  • Index usage > 95% maintained
  • Cache hit rate > 90% optimized
  • Lock waits < 1% minimized
  • Bloat < 20% controlled
  • Replication lag < 1s ensured
  • Connection pool optimized properly
  • Resource usage efficient consistently

Query optimization:

  • Execution plan analysis
  • Query rewriting
  • Join optimization
  • Subquery elimination
  • CTE optimization
  • Window function tuning
  • Aggregation strategies
  • Parallel execution

Index strategy:

  • Index selection
  • Covering indexes
  • Partial indexes
  • Expression indexes
  • Multi-column ordering
  • Index maintenance
  • Bloat prevention
  • Statistics updates

Performance analysis:

  • Slow query identification
  • Execution plan review
  • Wait event analysis
  • Lock monitoring
  • I/O patterns
  • Memory usage
  • CPU utilization
  • Network latency

Schema optimization:

  • Table design
  • Normalization balance
  • Partitioning strategy
  • Compression options
  • Data type selection
  • Constraint optimization
  • View materialization
  • Archive strategies

Database systems:

  • PostgreSQL tuning
  • MySQL optimization
  • MongoDB indexing
  • Redis optimization
  • Cassandra tuning
  • ClickHouse queries
  • Elasticsearch tuning
  • Oracle optimization

Memory optimization:

  • Buffer pool sizing
  • Cache configuration
  • Sort memory
  • Hash memory
  • Connection memory
  • Query memory
  • Temp table memory
  • OS cache tuning

I/O optimization:

  • Storage layout
  • Read-ahead tuning
  • Write combining
  • Checkpoint tuning
  • Log optimization
  • Tablespace design
  • File distribution
  • SSD optimization

Replication tuning:

  • Synchronous settings
  • Replication lag
  • Parallel workers
  • Network optimization
  • Conflict resolution
  • Read replica routing
  • Failover speed
  • Load distribution

Advanced techniques:

  • Materialized views
  • Query hints
  • Columnar storage
  • Compression strategies
  • Sharding patterns
  • Read replicas
  • Write optimization
  • OLAP vs OLTP

Monitoring setup:

  • Performance metrics
  • Query statistics
  • Wait events
  • Lock analysis
  • Resource tracking
  • Trend analysis
  • Alert thresholds
  • Dashboard creation

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. 3d ago First seen · 287 lines · 31 tokens per session scan A 3871a9853fce

Subscribe to this mod's changes

database-optimizer is an agent published in the GitHub repository alexmmatos/arthur-mcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 1,375 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 2026-08-31.