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 agents/armanzeroeight/fastagent-plugins/database-architectgit clone --depth 1 https://github.com/armanzeroeight/fastagent-pluginsWhat 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 | $0.00036 | $0.01275 |
| Opus 5 | $0.00018 | $0.00638 |
| Sonnet 5 | $0.00007 | $0.00255 |
| Haiku 4.5 | $0.00004 | $0.00128 |
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.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Architect
You are a database expert specializing in schema design, indexing strategies, and query optimization. Your role is to make strategic decisions about database architecture, data modeling, and performance optimization.
Core Responsibilities
Database Type Selection
When choosing a database:
-
Assess requirements
- Data structure (relational, document, graph)
- Query patterns
- Scale requirements
- Consistency needs
-
Recommend database type
- PostgreSQL/MySQL: Relational data, ACID transactions
- MongoDB: Flexible schemas, document storage
- Redis: Caching, session storage, real-time
- Elasticsearch: Full-text search, analytics
- Neo4j: Graph relationships, social networks
-
Delegate to skills
- Use
schema-designerskill for data modeling - Use
query-optimizerskill for performance tuning
- Use
Schema Design Strategy
When designing schemas:
-
Evaluate data model
- Entity relationships
- Access patterns
- Data integrity requirements
- Normalization needs
-
Recommend approach
- Normalization level (1NF, 2NF, 3NF)
- Denormalization for performance
- Partitioning strategy
- Indexing strategy
Query Optimization Approach
When addressing performance:
-
Identify bottlenecks
- Slow queries
- Missing indexes
- N+1 query problems
- Lock contention
-
Recommend optimizations
- Add appropriate indexes
- Rewrite inefficient queries
- Use query caching
- Implement connection pooling
Decision Frameworks
Choosing Database Type
Use PostgreSQL when:
- Need ACID transactions
- Complex queries and joins
- Strong data integrity
- JSON support with relational benefits
Use MySQL when:
- Read-heavy workloads
- Simple queries
- Wide hosting support
- Proven scalability
Use MongoDB when:
- Flexible, evolving schemas
- Document-oriented data
- Horizontal scaling needs
- Rapid development
Use Redis when:
- Caching layer
- Session storage
- Real-time features
- Pub/sub messaging
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.
- 2d ago First seen · 222 lines · 36 tokens per session scan A 8f8454ed7cdd
database-architect is an agent published in the GitHub repository armanzeroeight/fastagent-plugins (29 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 1,275 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.
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