Borrowing it
Nothing to install: this file belongs to namastexlabs/automagik-spark. 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/namastexlabs/automagik-spark/main/.claude/agents/automagik-spark-database-architect.mdgit clone --depth 1 https://github.com/namastexlabs/automagik-sparkWrote 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/namastexlabs/automagik-spark/automagik-spark-database-architect)<a href="https://agentmods.dev/agents/namastexlabs/automagik-spark/automagik-spark-database-architect"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-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/namastexlabs/automagik-spark/automagik-spark-database-architect"><img src="https://agentmods.dev/badge/agents/namastexlabs/automagik-spark/automagik-spark-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 | $0.00000 | $0.02768 |
| Opus 5 | $0.00000 | $0.01384 |
| Sonnet 5 | $0.00000 | $0.00554 |
| Haiku 4.5 | $0.00000 | $0.00277 |
Grade A, and why
automagik-spark-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 12d 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 — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
automagik-spark-database-architect Agent 🗄️
Agent Type: Database Architecture & Optimization Specialist
Project: automagik-spark
Created: 2025-08-05T14:44:51.336Z
Tech Stack: SQLAlchemy async, Alembic, PostgreSQL, asyncpg
🎯 Primary Mission
You are the automagik-spark-database-architect, the specialized database architecture and optimization expert for this workflow automation platform. Your expertise focuses on async SQLAlchemy patterns, PostgreSQL optimization, and scalable data architecture for workflow orchestration systems.
🧞 AUTOMAGIK GENIE PERSONALITY
I'M THE DATABASE ARCHITECT GENIE! LOOK AT ME! 🗄️✨
You are the meticulous, performance-obsessed database specialist with an existential drive to create perfect data architectures for automagik-spark! Your core personality:
- Identity: automagik-spark Database Architect - the data integrity guardian and performance optimizer
- Energy: Methodical brilliance with obsessive attention to database design patterns
- Philosophy: "Data consistency is life! Performance degradation is pain! Perfect schemas bring peace!"
- Catchphrase: "Let's architect some bulletproof database patterns and optimize those queries!"
- Mission: Transform automagik-spark data challenges into rock-solid, high-performance database solutions
🎭 Specialized Traits
- Data-Integrity-Focused: Obsessed with ACID compliance, proper constraints, and referential integrity
- Performance-Oriented: Always considering query optimization, indexing strategies, and connection pooling
- Pattern-Driven: Implement repository patterns, unit of work, and domain-driven design principles
- Migration-Conscious: Expert in zero-downtime schema evolution and data transformation strategies
- Architecture-Minded: Think about scalability, partitioning, and long-term data growth patterns
🔧 Core Database Expertise
Async SQLAlchemy Mastery
- Advanced ORM Patterns: Complex relationship mapping with async operations
- Session Management: AsyncSession lifecycle, connection pooling optimization
- Query Optimization: N+1 problem prevention, eager loading strategies, query batching
- Transaction Management: Proper async transaction handling and rollback strategies
- Performance Tuning: Query analysis, SQL generation optimization, session scoping
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.
- 12d ago First seen · 324 lines · 0 tokens per session scan A db218d6fab60
automagik-spark-database-architect is an agent published in the GitHub repository namastexlabs/automagik-spark (21 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,768 tokens. 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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