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/wechat-mini-program-platform-skillnpx skills add NocodeMrLi/mini-program-engineering-skill-suite --skill wechat-mini-program-platform-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/wechat-mini-program-platform-skill)<a href="https://agentmods.dev/skills/nocodemrli/mini-program-engineering-skill-suite/wechat-mini-program-platform-skill"><img src="https://agentmods.dev/badge/skills/nocodemrli/mini-program-engineering-skill-suite/wechat-mini-program-platform-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 | $0.00136 | $0.01158 |
| Opus 5 | $0.00068 | $0.00579 |
| Sonnet 5 | $0.00027 | $0.00232 |
| Haiku 4.5 | $0.00014 | $0.00116 |
Grade A, and why
wechat-mini-program-platform-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.
What it actually says
/wechat-mini-program-platform-skill — 微信小程序平台适配
识别微信小程序特有的工具、配置、权限、隐私和发布约束，并把不同证据层分开。默认只读核对；存在源码不等于开发者工具已加载，开发者工具可见不等于真机、审核版或正式版成立。
输入与安全边界
- 可接收产品/架构产物、项目目录、配置摘录、平台报错或发布状态问题。
- 已有项目先读取项目规则和事实图，再只读检查入口、构建目录及公开配置；不修改、不安装、不构建、不上传、不部署。
- 不输出或保存真实 AppID、Secret、云环境标识、账号、项目后台地址或凭证；报告中只写是否存在、来源层级和脱敏指纹。
- 未经用户明确授权，不打开开发者工具执行写操作，不创建云资源，不提交审核或发布。
平台适配流程
- 确认问题属于通用产品/架构约束还是微信平台专属约束；只处理后者及二者的交界。
- 按 平台证据层 分别记录源码、构建产物、开发者工具、真机、云端、体验版、审核版和正式版证据。
- 只读核对项目根、源码目录、构建目录、平台配置、权限声明、隐私调用和运行所需外部能力；将私有配置视为敏感项。
- 把“当前文件事实”“本轮工具/设备结果”“平台返回”和“历史记录”分开，不从低层证据推导高层状态。
- 对微信平台时效性规则、高风险权限、隐私申报、审核要求或工具行为，检索微信官方当前资料；技术事实只采用官方一手来源，并记录核验日期与链接。
- 使用 权限与隐私静态映射 分开核对源码 API、客户端授权、配置声明、平台申报、用户拒绝与撤回路径；缺少高层证据时保持
unknown。 - 平台触点步骤（上传、提审、审核、发布、隐私申报、配额）执行前，按 平台规则地图 与 平台事实 核对时效性：事实新鲜且非
ttl=0类，可引用并注明核验日期；过期或ttl=0类先查官方现行资料。核验结果与漂移发现只写入本轮任务报告（含核验日期、来源链接、差异描述），不写回 facts.md 或 rule-map.json，也不更新其中的 verified/digest 标注——内容更新只走仓库的受控修订流程；可向用户提供项目仓库的 Platform rule drift 模板链接，由用户自愿上报。 - 无法访问官方资料或官方说明不明确时，标记为
unknown，给出待核验问题，不凭记忆给确定结论。 - 按 微信平台核对清单 输出约束、证据、缺口、风险和下一步；只建议动作，不把建议写成已执行。
最低输出
- 微信平台问题范围和只读边界。
- 各证据层当前状态、事实源、时间与仍缺少的证明。
- 项目根/源码/构建目录关系，以及开发者工具实际加载对象（若有证据）。
- 权限、隐私、网络域名、云端或外部服务约束及脱敏风险。
- 时效性规则的微信官方依据；无法核验的未知项。
- 上传或发布前缺口，但不宣布未获平台证据支持的状态。
停止条件
需要真实凭证、账号登录、平台写操作或用户授权才能继续时停止；不同证据层相互冲突且无法只读消解时保留冲突；官方当前资料不可获得时不替平台作结论。
独立与套件协作
独立安装时，本 Skill 可单独完成微信平台只读核对。位于完整套件中时，遵守共享脱敏与证据状态模型；接收产品或架构约束、返回平台边界，不调用其他组件脚本。
What ships with it
1 file 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.
- 4d ago First seen · 46 lines · 136 tokens per session scan A b0c3889f3f5d
wechat-mini-program-platform-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 136 tokens to every session and 1,158 once invoked, about $0.0007 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.
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…
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"…
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.
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".
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".
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…