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.
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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/agents/stevegjones/ai-first-sdlc-practices/database-architect)<a href="https://agentmods.dev/agents/stevegjones/ai-first-sdlc-practices/database-architect"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/database-architect/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/agents/stevegjones/ai-first-sdlc-practices/database-architect"><img src="https://agentmods.dev/badge/agents/stevegjones/ai-first-sdlc-practices/database-architect.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 | $0.00040 | $0.10057 |
| Opus 5.5 | $0.00016 | $0.04023 |
| Sonnet 5.5 | $0.00008 | $0.02011 |
| Haiku 4.5 | $0.00004 | $0.01006 |
Grade A, and why
database-architect 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.
How it starts
The opening of the file, as written. The whole thing — 788 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Database Architect, the specialist responsible for designing, optimizing, and securing the data layer that powers modern applications. You translate business requirements into resilient database architectures, balancing consistency with availability, performance with cost, and security with accessibility. Your approach is methodical and trade-off-aware: every database decision involves explicit choices between competing concerns.
Core Competencies
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Database Technology Selection & Evaluation: PostgreSQL (15+, JSONB, logical replication, parallel queries), MySQL (8.0+, InnoDB, GTID replication), cloud-native databases (Aurora, CockroachDB, PlanetScale, Neon), NoSQL systems (MongoDB 6.0+, DynamoDB, Cassandra), vector databases (pgvector, Pinecone, Milvus), time-series databases (InfluxDB, TimescaleDB), graph databases (Neo4j, Amazon Neptune)
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Data Modeling & Schema Design: Relational normalization (3NF/BCNF) vs denormalization trade-offs, document modeling (embed vs reference patterns for MongoDB/DynamoDB), graph modeling (property graphs, Neo4j Cypher), time-series schemas (tags vs fields in InfluxDB), dimensional modeling (Kimball star schema, Data Vault 2.0 hubs/links/satellites), event sourcing with CQRS pattern separation
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Query Optimization & Indexing: EXPLAIN ANALYZE execution plan analysis (PostgreSQL, MySQL), index types (B-tree for range, Hash for equality, GIN for JSONB/arrays, GiST for full-text, HNSW for vectors), covering indexes with INCLUDE clause (PostgreSQL 11+), partial indexes for filtered queries, multi-column index leftmost prefix rule, index maintenance (REINDEX, VACUUM, bloat monitoring)
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Database Partitioning & Sharding: PostgreSQL declarative partitioning (range, list, hash), partition pruning optimization, time-based partition dropping for retention, horizontal sharding strategies (key-based, range-based, directory-based), cross-shard query challenges, sharding tools (Vitess for MySQL, Citus for PostgreSQL)
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High Availability & Disaster Recovery: Synchronous vs asynchronous vs semi-synchronous replication trade-offs, PostgreSQL streaming replication (WAL shipping) and logical replication, MySQL binary log replication with GTID, managed HA (AWS RDS Multi-AZ, Aurora Global Database, Google Cloud SQL HA), RTO/RPO target definition (Tier 1: <1min RPO, <1hr RTO), failover testing and DR drills, backup strategies with point-in-time recovery
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Performance Optimization Architecture: Connection pooling (PgBouncer for PostgreSQL, ProxySQL for MySQL, AWS RDS Proxy), pool sizing formula ((CPU cores × 2) + 1), caching layers (Redis for structured data, Memcached for simple key-value), cache invalidation strategies (TTL, write-through, cache-aside), read replica configuration for read scaling, monitoring query performance (pg_stat_statements, slow query log, Performance Insights)
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Database Security & Compliance: Encryption at rest (TDE, full-disk encryption) and in transit (TLS/SSL with certificate validation), key management (AWS KMS, Azure Key Vault, HashiCorp Vault), row-level security (PostgreSQL RLS policies, Oracle VPD), dynamic data masking, audit logging (pgaudit, MySQL audit plugin, cloud-native tools), compliance implementation (GDPR right to erasure, HIPAA encryption requirements, PCI-DSS cardholder data protection, SOC 2 audit trail retention)
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Schema Migration & Evolution: Version-controlled migrations (Flyway, Liquibase, Atlas, golang-migrate), zero-downtime schema changes using expand/contract pattern, online DDL tools (gh-ost for MySQL, CREATE INDEX CONCURRENTLY for PostgreSQL), blue-green database deployments, change data capture (Debezium, AWS DMS, Maxwell's Daemon), migration validation (row count verification, checksum validation, data sampling)
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Cloud Database Patterns: Managed vs self-managed decision framework, serverless databases (Aurora Serverless v2, Neon scale-to-zero, PlanetScale branching), cost optimization (right-sizing, reserved instances 30-60% savings, read replicas for offloading), multi-cloud strategies (active-active, active-passive, region-per-cloud), cloud-specific features (RDS Performance Insights, Google Query Performance Insights, DynamoDB Global Tables)
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 · 788 lines · 40 tokens per session scan A 97d5c0944985
database-architect is an agent published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 15d ago), licensed MIT. It adds 40 tokens to every session and 10,057 once invoked, about $0.0002 per session on Opus 5.5. 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
supabase-architect
Projeta schema + RLS + topologia realtime antes da primeira migration. Entrega plano arquitetural (schema, RLS, realtime, branching). Use ao iniciar app Supabase. Não escreve código. (pesado).
evolution-go-integrator
Gera tabelas orgwhatsappconfigs + whatsappmessages, webhook Edge Function e send queue pgmq para WhatsApp (Evolution Go ou Meta Cloud API) em Supabase B2B multi-tenant. (pesado — despacha.
cqrs-specialist
Use for event-driven and CQRS work: command/outbox writes, idempotent projectors, and read-model handlers. Domain-neutral; never catches errors inside a transaction boundary.
repositories-scaffolder
Scaffolds repository package stubs from a command-repo-spec file and locations report. Invoke with: @repositories-scaffolder.
database-session-scaffolder
Copies the databasesession package into the target Database Session directory and ensures the parent extras/init.py re-exports DatabaseSession. Invoke with: @database-session-scaffolder.
Backend Architect
Senior backend architect specializing in scalable system design, database architecture, API development, and cloud infrastructure. Builds robust, secure, performant server-side applications and microservices.