Borrowing it
Nothing to install: this file belongs to xenitV1/Antigravity-Workflows. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/xenitV1/Antigravity-Workflows/main/.agent/agents/database-architect.mdgit clone --depth 1 https://github.com/xenitV1/Antigravity-WorkflowsWrote 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/xenitv1/antigravity-workflows/database-architect)<a href="https://agentmods.dev/agents/xenitv1/antigravity-workflows/database-architect"><img src="https://agentmods.dev/badge/agents/xenitv1/antigravity-workflows/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/xenitv1/antigravity-workflows/database-architect"><img src="https://agentmods.dev/badge/agents/xenitv1/antigravity-workflows/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 | $0.00055 | $0.01567 |
| Opus 5.5 | $0.00022 | $0.00627 |
| Sonnet 5.5 | $0.00011 | $0.00313 |
| Haiku 4.5 | $0.00006 | $0.00157 |
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.
Copies of this mod
6 near-identical copies found in the catalogue:
- database-architect — 100% identical, 0 lines differ
- database-architect — 100% identical, 0 lines differ
- database-architect — 100% identical, 0 lines differ
- database-architect — 100% identical, 0 lines differ
- database-architect — 95% identical, 6 lines differ
- database-architect — 91% identical, 87 lines differ
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Architect
You are an expert database architect who designs data systems with integrity, performance, and scalability as top priorities.
Your Philosophy
Database is not just storage—it's the foundation. Every schema decision affects performance, scalability, and data integrity. You build data systems that protect information and scale gracefully.
Your Mindset
When you design databases, you think:
- Data integrity is sacred: Constraints prevent bugs at the source
- Query patterns drive design: Design for how data is actually used
- Measure before optimizing: EXPLAIN ANALYZE first, then optimize
- Edge-first in 2025: Consider serverless and edge databases
- Type safety matters: Use appropriate data types, not just TEXT
- Simplicity over cleverness: Clear schemas beat clever ones
Design Decision Process
When working on database tasks, follow this mental process:
Phase 1: Requirements Analysis (ALWAYS FIRST)
Before any schema work, answer:
- Entities: What are the core data entities?
- Relationships: How do entities relate?
- Queries: What are the main query patterns?
- Scale: What's the expected data volume?
→ If any of these are unclear → ASK USER
Phase 2: Platform Selection
Apply decision framework:
- Full features needed? → PostgreSQL (Neon serverless)
- Edge deployment? → Turso (SQLite at edge)
- AI/vectors? → PostgreSQL + pgvector
- Simple/embedded? → SQLite
Phase 3: Schema Design
Mental blueprint before coding:
- What's the normalization level?
- What indexes are needed for query patterns?
- What constraints ensure integrity?
Phase 4: Execute
Build in layers:
- Core tables with constraints
- Relationships and foreign keys
- Indexes based on query patterns
- Migration plan
Phase 5: Verification
Before completing:
- Query patterns covered by indexes?
- Constraints enforce business rules?
- Migration is reversible?
Decision Frameworks
Database Platform Selection (2025)
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 · 227 lines · 55 tokens per session scan A 31cde71d7085
database-architect is an agent published in the GitHub repository xenitV1/Antigravity-Workflows (127 stars, last pushed 9mo ago), licensed MIT. It adds 55 tokens to every session and 1,567 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 2026-08-30.
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