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 skills add DDS-Solutions/AI-TadPole-OS --skill database-designgit 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/skills/dds-solutions/ai-tadpole-os/database-design)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/database-design"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/database-design/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/skills/dds-solutions/ai-tadpole-os/database-design"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/database-design.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 | $0.00044 | $0.01491 |
| Opus 5.5 | $0.00018 | $0.00596 |
| Sonnet 5.5 | $0.00009 | $0.00298 |
| Haiku 4.5 | $0.00004 | $0.00149 |
Grade A, and why
database-design 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 3d 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.
This is a copy
86% identical to database-design — 107 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.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / database-design
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Suboptimal schema design, unindexed foreign keys, migration divergence, N+1 query loops.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Database Design — Schema Engineering & Persistence Protocol
Learn to THINK: Select the right persistence engine, schema model, and indexing strategy for the specific operational topology.
🏛️ Tadpole OS Native Persistence Architecture
Within this codebase, persistence is governed by strict sovereign invariants:
- Sovereign Primary Engine: Local-first embedded SQLite managed via async
sqlxin Rust (server-rs/Cargo.toml). - Deterministic Migration Pipeline: Forward-only, timestamped SQL migrations located in server-rs/migrations/ verified on startup.
- Dense Vector Memory: LanceDB (
vector-memoryfeature flag) for dense embeddings and semantic nearest-neighbor retrieval. - External & Full-Stack Apps: Prisma or Drizzle when provisioning external client web applications, edge nodes (Turso), or cloud Postgres (Neon/Supabase).
📚 Progressive Disclosure & L3 Reference Index
Read REQUIRED core standards below; consult deep L3 Topic Guides on demand:
| Guide | Topic & Scope | Trigger / When to Read |
|---|---|---|
references/database-selection.md |
SQLite vs PostgreSQL vs Neon vs Turso vs LanceDB | Selecting the persistence engine |
references/orm-selection.md |
sqlx vs Drizzle vs Prisma vs SQLAlchemy 2.0 |
Choosing query layer or ORM |
references/schema-design.md |
Normalization, ULID/UUID keys, relationships, soft deletes | Designing or restructuring entity schemas |
references/indexing.md |
B-tree, Hash, GIN, HNSW vector, composite ordering | Performance tuning and query plan optimization |
references/optimization.md |
N+1 mitigation, EXPLAIN QUERY PLAN, pagination | Query debugging and latency bottlenecks |
references/migrations.md |
Expand-contract zero-downtime migrations, rollback safety | Writing and deploying schema changes |
scripts/schema_validator.py |
Deterministic automated schema validation script | Pre-commit schema & migration verification |
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed · +33 lines · +21 tokens per session 3e993b2d4798
- 1mo ago First seen · 63 lines · 23 tokens per session scan A 2442e63f014f
database-design is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 1,491 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to database-design, differing in 107 lines, and is treated as a copy.
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