Borrowing it
Nothing to install: this file belongs to AsiaOstrich/EngramGraph. 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/AsiaOstrich/EngramGraph/main/.agents/skills/database-assistant/SKILL.mdgit clone --depth 1 https://github.com/AsiaOstrich/EngramGraphWrote 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/asiaostrich/engramgraph/database-assistant)<a href="https://agentmods.dev/skills/asiaostrich/engramgraph/database-assistant"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/database-assistant/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/asiaostrich/engramgraph/database-assistant"><img src="https://agentmods.dev/badge/skills/asiaostrich/engramgraph/database-assistant.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 | $0.00068 | $0.01283 |
| Opus 5.5 | $0.00027 | $0.00513 |
| Sonnet 5.5 | $0.00014 | $0.00257 |
| Haiku 4.5 | $0.00007 | $0.00128 |
Grade A, and why
database 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 14d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Assistant | 資料庫助手
Guide database design, migration planning, and query optimization.
引導資料庫設計、遷移規劃和查詢最佳化。
Core Principles | 核心原則
| Principle | Description | 說明 |
|---|---|---|
| Normalization | Eliminate redundancy (3NF minimum) | 消除冗餘（至少 3NF） |
| Referential Integrity | Enforce FK constraints | 強制外鍵約束 |
| Index Strategy | Index query patterns, not all columns | 依查詢模式建立索引 |
| Migration Safety | Always reversible, zero-downtime | 可逆、零停機 |
| Data Protection | Encrypt sensitive fields, audit access | 加密敏感欄位、稽核存取 |
Schema Design Checklist | Schema 設計檢查清單
- Primary keys defined (prefer UUID or BIGINT) | 主鍵已定義
- Foreign keys with proper ON DELETE/UPDATE | 外鍵含適當的級聯策略
- NOT NULL constraints on required fields | 必填欄位加 NOT NULL
- Indexes on frequently queried columns | 常查詢欄位建立索引
- Created/Updated timestamps on all tables | 所有表加建立/更新時間戳
- Sensitive data encrypted at rest | 敏感資料靜態加密
- Naming conventions consistent (snake_case) | 命名慣例一致（snake_case）
Normalization Quick Reference | 正規化快速參考
| Normal Form | Rule | 規則 |
|---|---|---|
| 1NF | Atomic values, no repeating groups | 原子值、無重複群組 |
| 2NF | 1NF + no partial dependencies | 1NF + 無部分相依 |
| 3NF | 2NF + no transitive dependencies | 2NF + 無遞移相依 |
| Denormalize | Only for proven read performance needs | 僅針對已證實的讀取效能需求 |
Migration Workflow | 遷移工作流程
PLAN ──► WRITE ──► TEST ──► DEPLOY ──► VERIFY
1. Plan — Assess Impact | 評估影響
Identify affected tables, estimate data volume, plan rollback strategy.
識別受影響的表、估算資料量、規劃回滾策略。
2. Write — Create Migration | 撰寫遷移
Write forward and rollback scripts. Use incremental, numbered migrations.
撰寫正向和回滾腳本。使用遞增編號的遷移。
3. Test — Validate Migration | 驗證遷移
Run on staging with production-like data. Verify data integrity post-migration.
在 staging 環境使用類生產資料執行。驗證遷移後資料完整性。
4. Deploy — Execute Migration | 執行遷移
Apply during maintenance window or use online schema change tools.
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.
- 14d ago First seen · 120 lines · 68 tokens per session scan A bf37b1dd1a46
database is a skill published in the GitHub repository AsiaOstrich/EngramGraph (3 stars, last pushed today), licensed MIT. It adds 68 tokens to every session and 1,283 once invoked, about $0.0003 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 2026-10-16.
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