nanzi-ai-agent-platform: Skill for Claude Code

.agent/skills/dev-skills/SKILL.md

dev-skills is a skill for Claude Code, Codex from RandyChen1985/nanzi-ai-agent-platform. It costs 29 tokens per session (1,105 once invoked), scanned A, original, MIT.

A set of development instructions tailored to one user's preferences. It defines Chinese communication rules, planning and documentation steps, local Git commit approvals, and user-controlled service startup.

In plain words
What is it for?
Use it to guide coding tasks, write Chinese plans and documents, manage commits, and control build or development-service workflows.
Why use it?
It keeps development work consistent with the user's language, planning, review, and release preferences. It also prevents the agent from pushing code or starting services without permission.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

This is RandyChen1985/nanzi-ai-agent-platform's own configuration. It tells Claude Code and Codex how to work on nanzi-ai-agent-platform itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything nanzi-ai-agent-platform configures →

Reuse

Borrowing it

Nothing to install: this file belongs to RandyChen1985/nanzi-ai-agent-platform. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/RandyChen1985/nanzi-ai-agent-platform/main/.agent/skills/dev-skills/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/RandyChen1985/nanzi-ai-agent-platform

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 dev-skills

README.md
[![agentmods](https://agentmods.dev/badge/skills/randychen1985/nanzi-ai-agent-platform/dev-skills/github.svg)](https://agentmods.dev/skills/randychen1985/nanzi-ai-agent-platform/dev-skills)
Your own site
<a href="https://agentmods.dev/skills/randychen1985/nanzi-ai-agent-platform/dev-skills"><img src="https://agentmods.dev/badge/skills/randychen1985/nanzi-ai-agent-platform/dev-skills/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.

agentmods 80×15 button for dev-skills

Your own site · 80×15
<a href="https://agentmods.dev/skills/randychen1985/nanzi-ai-agent-platform/dev-skills"><img src="https://agentmods.dev/badge/skills/randychen1985/nanzi-ai-agent-platform/dev-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,105 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00029 $0.01105
Opus 5 $0.00015 $0.00553
Sonnet 5 $0.00006 $0.00221
Haiku 4.5 $0.00003 $0.00111

Measured 4d ago against content hash d2d35d5f4fd0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

dev-skills 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.

.agent/skills/dev-skills/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dev Skills

此技能定义了用户偏好的开发流程和规范。请在所有任务中严格遵守以下规则。

1. 沟通与文档 (Communication & Documentation)

  • 核心原则:始终使用 中文 (Chinese) 与用户交流,无论是在对话中还是在生成的文档中。
  • OpenSpec 与需求文档
    • 创建或更新 OpenSpec 需求文件(如 proposal.md, design.md 等)时,必须使用 中文
    • task.mdimplementation_plan.md 等工件也必须使用中文编写。

2. 计划与原理解释 (Planning & Rationale)

在进行任何功能开发或 Bug 修复 之前,必须先确定计划。

  • 分级计划机制 (Tiered Planning)
    • 微小改动 (Trivial):如拼写修复、样式微调。可以在对话中直接解释 Why/How,获得确认后执行。
    • 常规任务 (Normal/Feature):涉及逻辑变动。必须创建 implementation_plan.md
    • 主动询问原则:在开始执行前,Agent 必须询问用户:“此任务是否需要创建正式的实现计划文件?”。
  • 创建/更新 Implementation Plan (若确定需要)
    • 使用 implementation_plan.md 详细列出修改计划。
    • 核心内容必须包含
      1. 为什么这么做 (Why):解释修改的动机、根本原因 (Root Cause) 或设计思路。
      2. 准备怎么搞 (How):详细的修改步骤、涉及的文件以及预期的效果。
      3. 为什么这么修改 (Rationale):针对具体的代码变动,解释选择此实现方式的原因。
  • 确认先行:在开始写代码之前,必须先让用户阅读并确认计划。

3. 代码提交规范 (Git Workflow)

  • 严禁自动推送:每次修改完成并提交代码时,除非用户下达了明确的 “Push” 或 “推送” 指令,否则 Agent 只允许在本地执行 git commit 提交,绝对禁止自动执行 git push 同步到远程
  • 提交确认:本地进行 git commit 前,也必须征得用户明确确认,严禁自动执行。

4. 开发环境与启停服务 (Development & Startup)

  • 严禁编译前端与执行启动脚本:代码修改完成后,Agent 绝对不得自己去编译前端(如 npm run build 等),也不得执行 ./dev.sh 等编译/启停脚本
  • 由用户主导编译与重启:所有的前端编译构建、服务启停、重载与日志观察均由用户在控制台手动完成(方便排查问题)。修改完成后,仅需通知用户代码已就绪,等待用户自行处理。

5. 代码推送与 PR 流程 (Push & PR Workflow)

当用户要求“提交代码并发布”、“Push”或“创建 PR”时,遵循以下流程:

  1. 检查与切换分支 (Branching)
    • 根据任务内容(Feature/Fix)生成新分支名(例如 feat/xxx),并使用 git checkout -b <new_branch> 切换。
  2. 推送到远程 (Pushing)
    • 执行 git push -u origin <new_branch>
  3. 创建 Pull Request (Automated PR)
    • 自动生成 PR 标题和详细描述,并尝试使用 gh pr create 创建。
  4. 分支清理 (Cleanup)
    • 在 PR 合并或发布流程结束后,Agent 必须主动询问或提醒用户清理已完成的功能分支。

6. 数据库与提示词变更规范 (Database & Prompt Changes)

  • 数据库变更 (Database Changes)
    • 执行边界 (Strict Boundary):凡涉及数据库 Schema 或数据变更,Agent 仅负责db-prod/ 目录下创建 SQL 脚本。严禁自动执行 SQL 语句或通过 Python 脚本直接修改数据库。
    • 命名规范:使用 V 开头 + 自增序号 + 描述(例如 V29-add_new_table.sql,必须检查目录下的当前最大序号并 +1)。
  • 提示词变更 (Prompt Changes)
    • 凡涉及系统提示词 (Prompts) 的新增或更新,必须在 architech/prompts/ 下操作并进行版本控制。
    • Agent 仅负责创建/更新文件,不负责自动同步到系统内部。

Read the full file on GitHub · 64 lines

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 Changed d2d35d5f4fd0
  2. 10d ago First seen · 64 lines · 29 tokens per session scan A 1413d80c1e05

Subscribe to this mod's changes

dev-skills is a skill published in the GitHub repository RandyChen1985/nanzi-ai-agent-platform (167 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 1,105 once invoked, about $0.0001 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.