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 kanfu-panda/pdlc-skills --skill pdlc-db-designgit clone --depth 1 https://github.com/kanfu-panda/pdlc-skillsWrote 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/kanfu-panda/pdlc-skills/pdlc-db-design)<a href="https://agentmods.dev/skills/kanfu-panda/pdlc-skills/pdlc-db-design"><img src="https://agentmods.dev/badge/skills/kanfu-panda/pdlc-skills/pdlc-db-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/kanfu-panda/pdlc-skills/pdlc-db-design"><img src="https://agentmods.dev/badge/skills/kanfu-panda/pdlc-skills/pdlc-db-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00008 | $0.00897 |
| Opus 5 | $0.00004 | $0.00449 |
| Sonnet 5 | $0.00002 | $0.00179 |
| Haiku 4.5 | $0.00001 | $0.00090 |
Grade A, and why
pdlc-db-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 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.
What it actually says
数据库设计
根据需求和 API 设计文档，创建数据库设计方案。
PDLC 前置检查（必须执行，不可跳过）
- 从用户输入中提取功能名称关键词
- 在
docs/01_requirements/prd/目录下搜索包含该关键词的 PRD 文档- 匹配新格式：
F<日期>-<编号>-*<关键词>*-prd.md - 匹配旧格式：
YYYYMMDD-*<关键词>*-prd.md - 同时检查文件内容中是否包含该关键词
- 匹配新格式：
- 未找到 → 输出以下信息后立即停止，不继续执行：
⛔ PDLC 守卫：未找到与「<功能名>」相关的 PRD 文档。 数据库设计必须基于已有的 PRD。请先运行： 👉 /pdlc-prd <需求描述> - 找到 → 提取功能ID（如
F20260326-090000），读取该 PRD 内容，继续执行
工作流程
- 阅读需求: 阅读找到的 PRD 文档
- 阅读 API 设计: 阅读
docs/02_design/api/下同功能ID的 API 设计文档（如有） - 梳理数据模型: 识别实体、属性、关系
- ER 图: 用文本方式描绘实体关系图
- 表结构定义: 逐表定义字段、类型、约束
- 索引设计: 根据查询场景设计索引
- 输出设计文档: 在
docs/02_design/database/下创建数据库设计文档
文档内容
- 文件名格式:
<功能ID>-<功能名>-db.md（如F20260326-090000-user-auth-db.md）- 若 PRD 为旧格式无功能ID，则使用旧格式
YYYYMMDD-<模块名>-db.md
- 若 PRD 为旧格式无功能ID，则使用旧格式
- 文档顶部必须包含 PDLC 追溯头：
<!-- PDLC-TRACE --> <!-- 功能ID: F20260326-090000 --> <!-- 功能名称: user-auth --> <!-- 阶段: 设计 --> <!-- 前置文档: docs/01_requirements/prd/F20260326-090000-user-auth-prd.md -->
ER 图格式
[用户] 1──N [订单] N──N [商品]
│ │
└───N [地址] [库存] 1─┘
表结构格式
| 字段 | 类型 | 可空 | 默认值 | 索引 | 描述 |
|---|
必须包含
- 公共字段约定（id、created_at、updated_at、deleted_at 等）
- 主键策略（自增/UUID/雪花ID）
- 软删除策略
- 分表分库策略（如数据量大）
- 数据迁移方案（DDL 变更脚本）
要求
- 字段命名使用 snake_case
- 枚举值必须有中文说明
- 考虑数据量增长后的性能影响
设计目标: $ARGUMENTS
本命令的 handoff 输出：
✅ 数据库设计文档 完成
📦 产出：docs/02_design/database/<功能ID>-<功能名>-db.md
👉 下一步：（本次流程结束，无后续）
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 · 95 lines · 8 tokens per session scan A 3f17b04bbc85
pdlc-db-design is a skill published in the GitHub repository kanfu-panda/pdlc-skills (13 stars, last pushed yesterday), licensed MIT. It adds 8 tokens to every session and 897 once invoked, about $0.0000 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 2026-08-31.
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