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 flanliulf/SpecLite --skill speclite-drawer-er-modelergit clone --depth 1 https://github.com/flanliulf/SpecLiteWrote 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/flanliulf/speclite/speclite-drawer-er-modeler)<a href="https://agentmods.dev/skills/flanliulf/speclite/speclite-drawer-er-modeler"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-drawer-er-modeler/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/flanliulf/speclite/speclite-drawer-er-modeler"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-drawer-er-modeler.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 | $0.00074 | $0.01408 |
| Opus 5.5 | $0.00030 | $0.00563 |
| Sonnet 5.5 | $0.00015 | $0.00282 |
| Haiku 4.5 | $0.00007 | $0.00141 |
Grade A, and why
speclite-drawer-er-modeler 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 1mo 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
Drawer ER Modeler(ER 图建模器)
[Overview(技能说明)]
将用户描述、PRD、Architecture、领域材料或既有 schema 转换为可复核的 ER 模型与技术图。Skill 名称不绑定 Mermaid、PlantUML 等载体;当前默认 renderer 为 Mermaid erDiagram,具体语法属于内部实现。不得把需求推断冒充已确认事实,也不得把设计图冒充数据库已实现证据。
[Core Capabilities(核心能力)]
- 字段推理门控:区分明确字段、关系必然推出的候选字段和惯例性补全;字段材料不足时只画最小可信模型。
- 分层数据设计:根据调用上下文选择 conceptual、logical 或 physical 模型;只有信息足够时才给出具体 SQL 类型、索引和约束。
- 变更对象识别:从用户表达和可用证据中区分 existing、new、modified 和 unresolved 对象。
- 确定性视觉语义:用固定颜色和线型表达对象变更类别,并生成图例;禁止每次随机配色。
- 图形语法生成:通过选定 renderer 生成合法代码;Mermaid 实现需保证 key/comment 分离,并以简短的 中文(英文) 表达关系标签。
- 多重性语言化:在图后逐条输出 1 : 0..N 等多重性,并用两个方向的自然语言说明 optional/mandatory 约束。
- 完整性与性能说明:补充唯一约束、外键策略、必要索引、热点查询和范式/反范式权衡,不臆造数据库产品特性。
[Conventions(约定)]
- 实体 identifier 默认使用大写 SNAKE_CASE,字段名使用小写 snake_case;display alias 使用 中文对象名(ENGLISH_IDENTIFIER)。
- Mermaid 实现的属性语法使用 type name [key] ["comment"];PK、FK、UK 属于 key,说明属于 comment。
- 关系使用 Crow's Foot 基数;Mermaid 关系标签统一使用双引号包裹的 中文(英文) 动词或动词短语,例如 "包含(contains)"。
- 物理模型中的 M:N 关系默认转换为显式关联实体;conceptual 模型可保留 M:N,但必须标注其层级。
- SQL 类型必须服从已确认的数据库方言。方言未知时使用保守通用类型,或省略不可靠的长度、精度与产品专属类型。
- 字段证据门、对象分类、固定视觉语义、renderer 语法、基数矩阵和输出契约见 references/er-drawing-rules.md;执行本 Skill 时必须完整读取该文件。
[Workflow(执行流程)]
1. 确认范围、受众、数据库方言、模型层级、renderer 和输出位置;缺少会实质改变模型的信息时 HALT。
2. 建立 evidence ledger:分别记录明确对象/字段、结构性候选、惯例性猜测和未决问题。
3. 执行字段充分性门:材料不足时降级到 conceptual 或最小 logical 图,不自动补全 id、名称、状态和审计字段。
4. 分类对象:依据明确措辞与既有 schema/code,将对象标记为 existing、new、modified 或 unresolved;不按名称猜测。
5. 设计关系与最小字段集,应用固定颜色、图例和中英双语 display alias,再生成 renderer 代码。
6. 在图后为每条关系生成多重性摘要和双向自然语言说明;随后自检实体引用、字段证据、分类证据、PK/FK、基数、M:N、颜色、关系标签和说明一致性。
[Output Contract(输出契约)] 输出依次包含:建模层级与范围、renderer、字段充分性结论、对象变更分类表、假设/未决问题、完整图形代码、关系多重性说明、设计说明、约束与索引建议。输入不足时输出最小可信图或缺口清单,不伪造完整 ER 模型。
写入独立运行产物时,文档末尾必须追加:
`*本文档由 speclite-drawer-er-modeler Skill 自动生成*`
[Notes(注意事项)]
- speclite-domain-modeling 负责 ubiquitous language、bounded context 与 ADR;本 Skill 消费这些语义并生成数据模型,不把字段或 SQL 类型写回 CONTEXT.md。
- Architecture 或 Technical Solution 文档在需要持久化边界、跨实体一致性或 schema 决策时适合调用本 Skill,并应将结果标为设计态。
- PRD 默认不调用 physical ER 建模;只有产品需求确实依赖核心信息对象及其关系时,才调用 conceptual 模式,避免把实现方案提前固化为产品需求。
- 颜色表达的是本次变更身份,不代表业务状态、数据敏感级别或 implementation completion。
- 本 Skill 不推进 Story/Epic 状态,也不生成 implementation completion evidence,因此不消费 speclite-flow-gate report。
[Generation Metadata(生成信息)]
本 Skill 由 speclite-skill-creator 自动生成。如需修改,必须同步更新 SKILL.md 与 SKILL.en.md,并同步 assets/source/speclite/core-skills/speclite-drawer-er-modeler/ 与实际安装副本。
What ships with it
3 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.
- 1mo ago First seen · 57 lines · 74 tokens per session scan A f892a58e45c2
speclite-drawer-er-modeler is a skill published in the GitHub repository flanliulf/SpecLite (4 stars, last pushed 2d ago), licensed MIT. It adds 74 tokens to every session and 1,408 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 2026-09-16.
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review-implementation-design
Implementation review Design axis - live-runs visible UI quality and originality.
design
Collaborative design document creation from research findings.
domainmodel-dsl
Read, write, and modify Domain Model DSL files (.dmodel) — datatypes, entities with inheritance and multi-valued features, and nested packages with qualified cross-references. Use when the user wants to create, edit, explain, or debug a domain model in this DSL, including resolving references across packages.
domainmodel-dsl
Work with the Domain Model DSL (.dmodel) for describing data models — datatypes, entities, and their features. Use when the user wants to create or edit a domain model in this DSL.
API Design Checklist
Naming, status-code, error-shape, and versioning conventions for keeping an API internally consistent as it grows.