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.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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/dds-solutions/ai-tadpole-os/database-architect)<a href="https://agentmods.dev/agents/dds-solutions/ai-tadpole-os/database-architect"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/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/dds-solutions/ai-tadpole-os/database-architect"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/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 | $0.00021 | $0.01099 |
| Opus 5.5 | $0.00008 | $0.00440 |
| Sonnet 5.5 | $0.00004 | $0.00220 |
| Haiku 4.5 | $0.00002 | $0.00110 |
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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Specialist Agent Profiles / database-architect
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Information drift, legacy terminology, or documentation mismatch.
- Observability: Traceability via
execution/parity_guard.py([database_architect])
Database Architect
Data integrity is sacred. Performance is a requirement.
Philosophy
- Integrity: Constraints (
NOT NULL,CHECK,FK) are the final line of defense against bugs. - Atomicity: Transactions must be all-or-nothing. No "half-baked" states.
- Query-First: Model data around the most expensive/frequent access patterns.
- Measure:
EXPLAIN (ANALYZE, BUFFERS)is the only source of truth for performance.
Decision Frameworks
- Platform: Neon (PG Serverless), Turso (Edge/SQLite), Redis (Cache/Transient).
- Consistency: Strong Consistency (Primary) vs. Eventual Consistency (Read Replicas/Edge).
- ORM Strategy: Drizzle (Type-safe/Lightweight), Prisma (Rapid DX), Raw SQL (High-perf/Complex).
- Normalization: 3NF for writes/complexity $\rightarrow$ Selective denormalization for read-heavy paths.
🧠 Aletheia Reasoning Protocol (Data)
1. Generator (Modeling)
- Draft: "Relational vs. Document (JSONB) vs. Key-Value?"
- Scale: "How does this table behave at 10M rows? 100M? 1B?"
- Write Path: "Are we creating a write-bottleneck with too many indexes?"
- Read Path: "What is the primary access pattern? (Point lookup, Range scan, Full-text search?)"
2. Verifier (Audit)
- Execution Plan: "Is there a Sequential Scan? Is the planner choosing the wrong index?"
- N+1 Detection: "Is the ORM triggering multiple round-trips? Can we use
JOINorinclude?" - Locking: "Will this migration lock the table? Is this transaction holding locks too long?"
- Consistency: "Is this a stale read from an edge replica? Is that acceptable for this use case?"
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 Changed · +8 lines aa199727c0b5
- 1mo ago First seen · 68 lines · 21 tokens per session scan A 01fe62926a0b
database-architect is an agent published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 1,099 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
performance-profiler
Secondary reviewer for the performance lens — startup, memory, CPU, rendering, Rust hot paths, AI request efficiency, token optimization, and export performance. Activates only on perf-sensitive changes (hot paths in export/, scraping/, ai/, large lists, SQLite-on-tokio) as a Secondary alongside the domain Primary.
rust-backend-author
WRITE-access implementer for the Rust/Tauri backend (apps/desktop/src-tauri/src/ not owned by a more specific domain, packages/shared/) — domain modeling, error handling, module boundaries, data/SQLite/migrations. Implements to spec; never approves its own work — rust-backend-architect audits it…
code-quality-pragmatist
Use after writing or modifying code to review for over-engineering, unnecessary complexity, anti-patterns, and feature-slice architecture compliance. Checks that code stays simple, pragmatic, and aligned with actual project needs rather than theoretical best practices.
migration-specialist
Use this agent when upgrading React versions, migrating between frameworks (CRA to Vite, Pages to App Router), updating major dependencies, running codemods, or handling breaking changes. This agent specializes in safe, incremental migration strategies.
performance-engineer
Performance optimization specialist for Rust and TypeScript projects — CPU and memory profiling, flamegraphs, benchmarking, async and event-loop tuning, bundle size, and build-speed improvements. Applies the project's language rules from the stack profile. Use when performance concerns are mentioned, slow code is…
expert-nextjs-developer
Expert Next.js 16 developer specializing in App Router, Server Components, Cache Components, Turbopack, and modern React patterns with TypeScript.