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Mini Program Verification Skill

Community
NocodeMrLi
mini-program-verification-skill

Verify mini-program implementations and fixes with risk-calibrated evidence across static checks, unit tests, integration tests, state matrices, simulators, real devices, cloud environments, and release artifacts. Use when users ask to test, validate, accept, regression-check, quality-check, confirm readiness, or determine whether a mini-program feature is actually complete. Binds results to a source and build fingerprint, records commands and observable evidence, separates passed, failed, blocked, and not-run layers, prioritizes the next highest-information check, and never converts local success into device, cloud, release, or formal acceptance claims.

Overview

PublisherNocodeMrLi
Repositorymini-program-engineering-skill-suite
Skill namemini-program-verification-skill
Stars
91
Forks
7
Bundled files
8
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NocodeMrLi on GitHub. Read the source before you install it.

Installation

Install the Mini Program Verification Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NocodeMrLi/mini-program-engineering-skill-suite/tree/main/skills/mini-program-verification-skill
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NocodeMrLi/mini-program-engineering-skill-suite.git /tmp/mini-program-engineering-skill-suite
mkdir -p .claude/skills
cp -r /tmp/mini-program-engineering-skill-suite/skills/mini-program-verification-skill .claude/skills/mini-program-verification-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mini Program Verification Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mini Program Verification Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mini Program Verification Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/mini-program-verification-skill — 小程序工程验证

固定版本/风险,逐层验证,按证据报告。

输入与版本指纹

  • 接收目标、验收标准、交接、事实图、复现入口和可用环境。
  • 记录已核实的分支/提交/文件哈希、构建/配置、工具/设备/云端环境与时间;匿名快照无 Git 时填 unknown,不借外层提交。
  • 分清本轮/既有改动,不清理、覆盖或计入无关变化。
  • 验收行为不明时退回规格;故障根因不明时退回调试。

风险分层验证

  1. 按目标、变更、共享契约、数据/权限/外部服务和历史缺陷建风险矩阵。
  2. 审计按短路径用工具枚举文件/目标;数量须由清单算出,否则不报。沿用户路径追踪输入→写入→读取→呈现;活动资源列创建、暂停、恢复、销毁,检查 onLoad→onShow→onHide→onShow→onUnload;纯函数正确不等于页面持续可用。
  3. 再核对全称注释/承诺:摘实际表达式并算反例。“不重复”查游标走完集合并再次前进;“追加不影响”用同一输入比较集合长度变化前后的索引;非法数值查 NaN、无穷和小数,重进查状态恢复。不能只建议未来补测试;未证实不得判无发现或确认承诺成立。报告以发现为主体,各域记有发现/未发现/证据不足。
  4. 标高严重度、关键错误或发布阻断前,核实完整性并完成机制反证闭环:调用实参、条件求值、实际分支/兜底、可观察后果,主动查找能推翻该机制的路径。部分快照未含引用只证明缺口;仅完整清单或实际构建/解析失败可证明真实缺失。未证实则区分事实与假设,降级或标记 unknown。
  5. 先做低成本反证,再按风险升级:静态检查、单元测试、集成测试、状态矩阵、真机验证、云端验证、发布验证。
  6. 每项记录实际命令或步骤、退出码、样本/设备、观察结果和证据位置;只写“测过了”不构成证据。
  7. 覆盖正常、空、错误、边界、重复、并发/乱序、恢复与回归;不凑无关测试。
  8. 留存失败证据,区分产品、实现、环境和证据问题;不改期望掩盖失败。
  9. 按 证据可采信规则 逐份核对来源、时间、版本、完整性、独立性、适用结论和不能证明的内容;质量标签不得用结论状态替代。
  10. 未知项目先运行只读 capability doctor(独立安装时同等探测),按 验证能力与适配矩阵 复用能力;不自动安装或执行候选命令。
  11. 多页面/流程/状态按 分维度质量覆盖合同 枚举唯一目标,以只读 check 拦基线漂移;用 质量证据矩阵 记基础/专项、包体/分包、首屏、错误和发布观察窗,按 验证工作流 与 验证证据报告 输出风险。

状态与证据边界

  • 静态检查或单元测试最多支持 locally-verified,不推出真机、云端或发布结论。
  • 模拟器截图不是设备证据;真机证据需绑定机型、系统、微信版本、步骤和截图/日志。
  • 云端证据需绑定环境、部署版本、真实请求与日志;本地桩不能替代。
  • 构建成功不等于已上传;已上传不等于审核通过或正式发布。
  • 自主验证不等于正式验收;没有用户明确确认时,报告“验证通过,待验收”,不写 accepted。

最低输出

  • 目标、范围、版本指纹、风险矩阵和验收行为。
  • 各验证层的已执行命令/步骤、结果、证据位置与失败详情。
  • 审计输出确定性文件/目标清单、点名领域覆盖表、高严重度/发布阻断发现的机制反证闭环。
  • 审计发现全称承诺时,逐条给出“承诺、实际表达式、边界输入或最小反例、结论”;不能计算的标为证据不足,不用测试建议代替核验。
  • 审计活动资源时,逐条给出创建、暂停、恢复、销毁的页面生命周期证据和断点。
  • 条件触发时的目标单元来源、基础/专项覆盖数、失败项、N/A 依据、金样指纹和 check 结果。
  • 未执行、被阻塞和不适用项目,以及为什么未执行。
  • 当前可支持的最高状态、残余风险、不可推出结论和下一项高信息量验证。
  • 截图/截断日志须记工具版本、时间、环境、步骤、证据/构建指纹及完整性;缺失填 unknown。
  • 逐份标 admissible / limited / not-admissible 及理由;没有专用字段时写入事实或限制,proven / not-proven 不能代替证据质量标签。
  • 逐份明判完整性与独立性(来源、采验关系、同源/独立观察、交叉支持或 unknown);哈希/未复核不代替独立性分析。

停止条件

真实账号、设备、凭证、云写入、付费或平台操作未获授权则停当前证据层;三种方法仍被同一外部条件阻塞则报告阻塞。不为“通过”扩大权限。

独立与套件协作

独立安装可验证已有交付;套件内接收目标、版本和验证入口,向发布治理传递证据报告;不执行上传、审核或发布。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mini Program Verification Skill AI skill do?

Verify mini-program implementations and fixes with risk-calibrated evidence across static checks, unit tests, integration tests, state matrices, simulators, real devices, cloud environments, and release artifacts. Use when users ask to test, validate, accept, regression-check, quality-check, confirm readiness, or determine whether a mini-program feature is actually complete. Binds results to a source and build fingerprint, records commands and observable evidence, separates passed, failed, blocked, and not-run layers, prioritizes the next highest-information check, and never converts local...

Why use Mini Program Verification Skill on TypingMind?

Because you install it once and use it with any model. Mini Program Verification Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mini Program Verification Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NocodeMrLi/mini-program-engineering-skill-suite/tree/main/skills/mini-program-verification-skill. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mini Program Verification Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mini Program Verification Skill?

As many as you like. As long as a model supports skills, you can use Mini Program Verification Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mini Program Verification Skill AI skill free?

Yes. It is published on GitHub by NocodeMrLi under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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