mini-program-verification-skill

mini-program-verification-skill is a skill for Claude Code, Codex from NocodeMrLi/mini-program-engineering-skill-suite. It costs 129 tokens per session (1,228 once invoked), scanned A, original, MIT.

A verification guide for WeChat Mini Programs, which are small apps that run inside WeChat. It checks implementations through layers such as static checks, tests, simulators, real devices, cloud environments, and release artifacts.

In plain words
What is it for?
Use it to define acceptance checks, build a risk-based verification matrix, run appropriate tests, record failures and evidence, and report what was or was not verified.
Why use it?
It prevents a successful local build or test from being mistaken for real-device, cloud, review, or production readiness. It records evidence and separates proven results from unknowns.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-verification-skill
Any agent
npx skills add NocodeMrLi/mini-program-engineering-skill-suite --skill mini-program-verification-skill
Clone the repo
git clone --depth 1 https://github.com/NocodeMrLi/mini-program-engineering-skill-suite

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for mini-program-verification-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-verification-skill.svg)](https://agentmods.dev/skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-verification-skill)
Your own site
<a href="https://agentmods.dev/skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-verification-skill"><img src="https://agentmods.dev/badge/skills/nocodemrli/mini-program-engineering-skill-suite/mini-program-verification-skill.svg" alt="Measured on agentmods" height="20"></a>
Per session 129 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,228 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00129 $0.01228
Opus 5 $0.00064 $0.00614
Sonnet 5 $0.00026 $0.00246
Haiku 4.5 $0.00013 $0.00123

Measured 4d ago against content hash 3d15a425c26f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mini-program-verification-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 4d 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.

skills/mini-program-verification-skill/SKILL.md · 52 lines

What it actually says

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

把“看起来完成”转成可复查的证据。先固定目标版本和风险,再逐层验证;已执行到哪一层,就只报告到哪一层。

输入与版本指纹

  • 接收功能目标、验收标准、实现/修复交接、项目事实图、复现入口和允许使用的环境。
  • 验证前记录当前分支、提交或文件哈希、源码状态、构建产物标记、配置开关、工具/设备/云端环境与时间。
  • 若工作区已有用户改动,先划分本轮目标与既有差异;不得清理、覆盖或把无关变化计入验证结论。
  • 没有稳定验收行为时退回产品规格;根因未知的故障退回调试,不用随机测试代替定位。

风险分层验证

  1. 从用户目标、变更面、共享契约、数据/权限/外部服务和历史缺陷建立风险清单与验证矩阵。
  2. 先运行低成本且能否定结论的检查,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。
  3. 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。
  4. 覆盖正常、空、错误、边界、重复操作、并发/乱序、恢复与回归;不为凑数量执行与风险无关的测试。
  5. 失败时保存最小失败证据,区分产品不符合、实现缺陷、测试环境阻塞和证据缺失;不通过修改测试期望掩盖失败。
  6. 使用 证据可采信规则 记录产生工具、格式、版本、时间、环境/版本指纹、完整性、适用结论和不能证明的内容,并对每份证据给出 admissible / limited / not-admissible 质量标签;质量标签描述证据可采信程度,不与 proven / not-proven 等状态词混用或互相替代。
  7. 对未知项目先运行套件提供的只读 capability doctor(若独立安装则执行同等只读探测),再按 验证能力与适配矩阵 复用现有能力;不自动安装或执行候选命令。
  8. 使用 质量证据矩阵 记录包体/分包、启动/首屏、运行错误与发布后观察窗,并按 验证工作流验证证据报告 输出已执行、未执行和残余风险。

状态与证据边界

  • 静态检查或单元测试成功最多支持 locally-verified,不推出真机验证、云端验证或发布验证。
  • 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。
  • 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。
  • 即使只评估截图转录或截断日志,也逐项输出采集工具、工具版本、时间、设备/环境、步骤、证据/构建指纹和完整性;缺失时必须明确写 unknown 或缺失,不能省略字段。

停止条件

需要真实账号、设备、凭证、云端写入、付费资源或平台操作但未获授权时停止在当前证据层;三次不同验证方法仍被同一外部条件阻塞时报告阻塞。不得为了得到“通过”结论扩大外部权限。

独立与套件协作

独立安装时可验证已有小程序交付。位于套件中时,接收实现/调试/UI 阶段的目标、版本和验证入口,向发布治理传递证据报告;不直接执行上传、审核或发布。

Files

What ships with it

6 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.

Changes

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.

  1. 4d ago First seen · 52 lines · 129 tokens per session scan A 3d15a425c26f

Subscribe to this mod's changes

mini-program-verification-skill is a skill published in the GitHub repository NocodeMrLi/mini-program-engineering-skill-suite (42 stars, last pushed 3d ago), licensed MIT. It adds 129 tokens to every session and 1,228 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.

Related

Other skills, from other repositories

nature-statistics

Audit, revise, or draft manuscript statistical reporting for Nature / high-impact journal submissions. Use when the user asks to check statistical analysis sections, p values, confidence intervals, sample size, biological versus technical replicates, randomization, blinding, multiple-comparison correction, model…

Yuan1z0825/nature-skills · 139 tokens

baoyu-youtube-transcript

Downloads YouTube video transcripts/subtitles and cover images by URL or video ID. Supports multiple languages, translation, chapters, and speaker identification. Caches raw data for fast re-formatting. Use when user asks to "get YouTube transcript", "download subtitles", "get captions", "YouTube字幕", "YouTube封面"…

JimLiu/baoyu-skills · 107 tokens

review-plan

Review a plan by running internal reviews and a peer review in parallel and returning combined findings. Use when the user asks to "review my plan", "check my plan", "critique my plan", or wants feedback on a plan.

tobihagemann/turbo · 50 tokens

reply-to-pr-threads

Draft, confirm, and post replies to GitHub PR review threads. Handles per-category reply formatting, re-fetches thread resolution state so auto-resolved threads are skipped, and posts via GraphQL. Use when the user asks to "reply to PR threads", "post PR thread replies", or "draft PR reply messages".

tobihagemann/turbo · 71 tokens

answer-reviewer-questions

For each reviewer question on a PR, recall implementation reasoning and compose a raw answer. Use when the user asks to "answer reviewer questions", "draft answers to PR questions", or "explain reviewer questions".

tobihagemann/turbo · 48 tokens

to-issues

Decompose a PRD and/or SPEC into implementable, vertically-sliced Issues with real blocking edges, then create them in your chosen platform (GitHub or Local). Use after /prd (and optionally /prd-to-spec) to turn requirements into agent-ready tickets. Triggers on: create issues, to-issues, 创建issue, 拆解issue, 生成卡片, 创建卡片…

smallnest/goal-workflow · 96 tokens