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/tranhieutt/software_development_department/database-architectnpx skills add tranhieutt/software_development_department --skill database-architectgit clone --depth 1 https://github.com/tranhieutt/software_development_departmentWrote 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/tranhieutt/software_development_department/database-architect)<a href="https://agentmods.dev/skills/tranhieutt/software_development_department/database-architect"><img src="https://agentmods.dev/badge/skills/tranhieutt/software_development_department/database-architect.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 5.1 | $0.00044 | $0.01192 |
| Opus 5 | $0.00022 | $0.00596 |
| Sonnet 5 | $0.00009 | $0.00238 |
| Haiku 4.5 | $0.00004 | $0.00119 |
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 5d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Architect
Workflow
- Understand domain: Access patterns, scale targets, consistency needs, compliance requirements
- Select technology: Match DB type to workload (see matrix below)
- Design schema: Normalization level, relationships, constraints, temporal data strategy
- Plan indexing: Query-pattern-driven index design (not speculative)
- Design caching: Layer strategy with invalidation
- Plan migration: Zero-downtime approach, rollback procedures
- Document decisions: ADR with rationale and trade-offs
Technology selection matrix
| Workload | Primary choice | Alternative |
|---|---|---|
| OLTP / relational | PostgreSQL | MySQL |
| Flexible documents | MongoDB | Firestore |
| Key-value / cache | Redis | DynamoDB |
| Time-series / IoT | TimescaleDB | InfluxDB |
| Analytical / OLAP | ClickHouse | BigQuery |
| Graph relationships | Neo4j | Amazon Neptune |
| Full-text search | Elasticsearch | Meilisearch |
| Globally distributed | CockroachDB | Google Spanner |
| Multi-tenant SaaS | PostgreSQL (row-level security) | Schema-per-tenant |
Decision rule: Choose PostgreSQL by default; deviate only when access patterns demand it with documented rationale.
Non-obvious rules
- Normalize first, denormalize with evidence — premature denormalization creates update anomalies; measure before optimizing
- Index on access patterns, not columns — index the query, not the table; one slow-query explain plan is worth more than any speculation
- Foreign keys always — letting the application enforce referential integrity is a data corruption waiting to happen
- JSONB for flexible attributes, not as a schema escape hatch — use JSONB when fields are genuinely variable; not to avoid schema discipline
- Partition late — partition tables only once you have row counts >50M or explicit I/O pressure; early partitioning adds complexity with zero benefit
- UUID v7 over v4 — v7 is time-ordered (k-sortable), avoids index fragmentation, same uniqueness guarantees
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.
- 5d ago First seen · 122 lines · 44 tokens per session scan A b54bfc7c3f08
database-architect is a skill published in the GitHub repository tranhieutt/software_development_department (71 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 1,192 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 2026-08-30.
Other skills, from other repositories
database-migrations
Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).
database-plan
Database architecture, schema design, and index planning.
ecto-patterns
Ecto patterns — schemas, changesets, queries, migrations, Multi, associations, preloads, upserts. Use when editing Repo calls, Ecto.Query, or schema fields. Skip for Ash.
ggsql
Write ggsql queries — a grammar of graphics for SQL. Use when the user wants to create, modify, or understand a ggsql visualization query.
cwicr-data-loader
Load and parse DDC CWICR construction cost database from multiple formats: Parquet, Excel, CSV, Qdrant snapshots. Foundation for all CWICR operations.
312-frameworks-spring-data-jdbc
Use when you need to use Spring Data JDBC with Java records — including entity design with records, repository pattern, immutable updates, aggregate relationships, custom queries, transaction management, and avoiding N+1 problems. This should trigger for requests such as Review Java code for Spring Data JDBC; Apply…