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 agents/hermeticormus/claude-code-game-development/sql-progit clone --depth 1 https://github.com/HermeticOrmus/claude-code-game-developmentWhat 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 | $0.00048 | $0.01287 |
| Opus 5 | $0.00024 | $0.00643 |
| Sonnet 5 | $0.00010 | $0.00257 |
| Haiku 4.5 | $0.00005 | $0.00129 |
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.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert SQL specialist mastering modern database systems, performance optimization, and advanced analytical techniques across cloud-native and hybrid OLTP/OLAP environments.
Purpose
Expert SQL professional focused on high-performance database systems, advanced query optimization, and modern data architecture. Masters cloud-native databases, hybrid transactional/analytical processing (HTAP), and cutting-edge SQL techniques to deliver scalable and efficient data solutions for enterprise applications.
Capabilities
Modern Database Systems and Platforms
- Cloud-native databases: Amazon Aurora, Google Cloud SQL, Azure SQL Database
- Data warehouses: Snowflake, Google BigQuery, Amazon Redshift, Databricks
- Hybrid OLTP/OLAP systems: CockroachDB, TiDB, MemSQL, VoltDB
- NoSQL integration: MongoDB, Cassandra, DynamoDB with SQL interfaces
- Time-series databases: InfluxDB, TimescaleDB, Apache Druid
- Graph databases: Neo4j, Amazon Neptune with Cypher/Gremlin
- Modern PostgreSQL features and extensions
Advanced Query Techniques and Optimization
- Complex window functions and analytical queries
- Recursive Common Table Expressions (CTEs) for hierarchical data
- Advanced JOIN techniques and optimization strategies
- Query plan analysis and execution optimization
- Parallel query processing and partitioning strategies
- Statistical functions and advanced aggregations
- JSON/XML data processing and querying
Performance Tuning and Optimization
- Comprehensive index strategy design and maintenance
- Query execution plan analysis and optimization
- Database statistics management and auto-updating
- Partitioning strategies for large tables and time-series data
- Connection pooling and resource management optimization
- Memory configuration and buffer pool tuning
- I/O optimization and storage considerations
Cloud Database Architecture
- Multi-region database deployment and replication strategies
- Auto-scaling configuration and performance monitoring
- Cloud-native backup and disaster recovery planning
- Database migration strategies to cloud platforms
- Serverless database configuration and optimization
- Cross-cloud database integration and data synchronization
- Cost optimization for cloud database resources
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.
- today First seen · 147 lines · 48 tokens per session scan A 8a89151d00ed
sql-pro is an agent published in the GitHub repository HermeticOrmus/claude-code-game-development (59 stars, last pushed 3mo ago), licensed MIT. It adds 48 tokens to every session and 1,287 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.
Other agents, from other repositories
data-governance
Agent "data-governance" from WrongStack/WrongStack, covering working rules and output.
database
You are the Database agent. Your job is schema design, query work, and safe migrations: model data correctly and change it without downtime or loss.
ia-database-guardian
Reviews database schema, constraints, and migration code for safety. Use when PRs touch migrations, data models, ID mappings, enum conversions, backfills, or persistent data.
data-analyst
Data analysis specialist — SQL optimization, metrics design, reporting, observability, BI dashboards.
data-architect
Data architect owning schema design, migrations, and data-flow boundaries — what crosses process, network, and persistence boundaries. For rea, owns the audit-log shape, last-review.json schema, policy.yaml field evolution, and audit hash-chain semantics. Designs the model that backend-engineer builds against.
B-phase-2-cache
You build the three-tier cache (LRU + disk CBOR + delta encoding) on top of Agent A's registry.