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 agentmods add skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-product-spec-skillnpx skills add NocodeMrLi/mini-program-engineering-skill-suite --skill mini-program-product-spec-skillgit clone --depth 1 https://github.com/NocodeMrLi/mini-program-engineering-skill-suiteWrote 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/nocodemrli/mini-program-engineering-skill-suite/mini-program-product-spec-skill)<a href="https://agentmods.dev/skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-product-spec-skill"><img src="https://agentmods.dev/badge/skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-product-spec-skill.svg" alt="Measured on agentmods" 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 | $0.00123 | $0.00843 |
| Opus 5 | $0.00062 | $0.00421 |
| Sonnet 5 | $0.00025 | $0.00169 |
| Haiku 4.5 | $0.00012 | $0.00084 |
Grade A, and why
mini-program-product-spec-skill 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 6d 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
/mini-program-product-spec-skill — 小程序产品规格
把模糊想法收敛为可交接、可验证的小程序产品规格。只定义“用户需要什么、在什么条件下发生什么”，不决定代码结构，也不直接实现页面。
输入与边界
- 可接收一句想法、需求记录、原型、现有页面说明或只读项目事实图。
- 先区分用户已确认事实、当前产品事实、有依据的假设、未知项和未来规划。
- 缺少的信息不会改变核心闭环时，采用最小且明确标注的假设继续；会实质性改变用户、价值、数据规则、付费、权限或主流程时，列为决策点。
- 不发明按钮、入口、奖励、社交、付费、广告、数据规则或异常处理来填满页面。
- 不决定代码结构、框架、数据库、API 形态或微信平台配置；这些分别交给架构和平台阶段。
规格流程
- 写出目标用户、发生场景、核心问题、用户期望结果和成功条件。
- 划定第一版最小闭环，分别记录
本版包含、本版不包含和未来候选。 - 用“触发 → 用户动作 → 系统反馈 → 状态变化 → 完成结果”描述主流程。
- 对无数据、加载中、失败、权限拒绝、重复操作、退出恢复和不可达条件补异常流程。
- 建立页面清单，只写页面职责、入口、出口和依赖的已确认状态，不写视觉或代码方案。
- 为关键页面和对象建立状态矩阵，明确状态来源、可见内容、允许动作和迁移条件。
- 将每条验收标准写成可观察行为；优先使用
Given / When / Then，避免“体验良好”“正常显示”等不可测试措辞。 - 使用 产品规格工作流 自检，再按 产品规格模板 交付。
最低输出
- 目标用户、核心问题、价值主张与成功条件。
- 已确认事实、假设、未知项和待用户决策项。
- 第一版范围、明确不做项与未来候选。
- 主流程、异常流程、页面职责与状态矩阵。
- 可测试验收标准，以及产品层仍未覆盖的风险。
- 交给架构阶段的稳定语义和不可擅自改变项。
停止条件
当核心用户、核心价值或关键数据规则存在互斥解释，且任一选择都会实质性改变主流程时，停止在决策点，不用假设替用户拍板。若用户要求直接编码但产品语义尚不稳定，先交付最小规格和阻塞项。
独立与套件协作
独立安装时，本 Skill 可单独产出产品规格。位于完整套件中时，遵守套件共享的事实优先、确认门禁、证据状态和脱敏规则；只把规格产物交给后续阶段，不调用其他组件脚本。
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.
- 6d ago First seen · 46 lines · 123 tokens per session scan A 9d7d764ffea3
mini-program-product-spec-skill is a skill published in the GitHub repository NocodeMrLi/mini-program-engineering-skill-suite (45 stars, last pushed 4d ago), licensed MIT. It adds 123 tokens to every session and 843 once invoked, about $0.0006 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 2026-08-30.
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