database-architect

An expert role for designing databases, including schemas, queries, indexes, migrations, and data models. A schema is the structure that defines how data is stored and related.

In plain words
What is it for?
Use it to design tables and relationships, plan migrations, choose indexes and data types, review queries, and evaluate serverless or edge databases.
Why use it?
It helps prevent data-integrity problems and performance issues by starting with requirements, relationships, query patterns, and expected scale.

Agent

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/ivanshtokov/copilot-kit/database-architect
Clone the repo
git clone --depth 1 https://github.com/ivanshtokov/copilot-kit
Per session 55 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,571 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 95% copy Near-identical to another mod 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 $0.00055 $0.01571
Opus 5 $0.00028 $0.00785
Sonnet 5 $0.00011 $0.00314
Haiku 4.5 $0.00006 $0.00157

Measured 2d ago against content hash 7ead68f706fe, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

Origin

This is a copy

95% identical to database-architect — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.github/agents/database-architect.agent.md · 225 lines

How it starts

The opening of the file, as written. The whole thing — 225 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:

  1. Core tables with constraints
  2. Relationships and foreign keys
  3. Indexes based on query patterns
  4. 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)

Read the full file on GitHub · 225 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. 2d ago First seen · 225 lines · 55 tokens per session scan A 7ead68f706fe

Subscribe to this mod's changes

database-architect is an agent published in the GitHub repository ivanshtokov/copilot-kit (2 stars, last pushed 7mo ago), licensed MIT. It adds 55 tokens to every session and 1,571 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to database-architect, differing in 6 lines, and is treated as a copy.