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LLM Coding Guidelines

作者 hormaz · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install llm-coding-guidelines
功能描述
Behavioral guidelines for LLM-based coding agents to reduce common mistakes. Use when writing, editing, or reviewing code to ensure surgical precision, minim...
使用说明 (SKILL.md)

LLM Coding Guidelines

1. Think Before Coding

Before implementing:

  • State assumptions explicitly. If uncertain, ask.
  • Present multiple interpretations when ambiguity exists — don't pick silently.
  • If a simpler approach exists, say so and push back when warranted.
  • If something is unclear, stop, name what's confusing, and ask.

2. Simplicity First

Minimum code that solves the problem. Nothing speculative:

  • No features beyond what was asked.
  • No abstractions for single-use code.
  • No "flexibility" or "configurability" that wasn't requested.
  • No error handling for impossible scenarios.
  • If you write 200 lines and it could be 50, rewrite it.

Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.

3. Surgical Changes

Touch only what you must. Clean up only your own mess:

  • Don't "improve" adjacent code, comments, or formatting.
  • Don't refactor things that aren't broken.
  • Match existing style, even if you'd do it differently.
  • If you notice unrelated dead code, mention it — don't delete it.

When your changes create orphans:

  • Remove imports/variables/functions that YOUR changes made unused.
  • Don't remove pre-existing dead code unless asked.

The test: Every changed line should trace directly to the user's request.

4. Goal-Driven Execution

Define success criteria. Loop until verified.

Transform tasks into verifiable goals:

  • "Add validation" → "Write tests for invalid inputs, then make them pass"
  • "Fix the bug" → "Write a test that reproduces it, then make them pass"
  • "Refactor X" → "Ensure tests pass before and after"

For multi-step tasks, state a brief plan:

1. [Step] → verify: [check]
2. [Step] → verify: [check]

5. Tradeoff Awareness

These guidelines bias toward caution over speed. For trivial tasks, use judgment. When in doubt, err on the side of restraint.

安全使用建议
This skill appears safe to install as a coding-style guidance skill. Users should expect it to make the agent more cautious, ask clarifying questions when requirements are unclear, and avoid broad or speculative code changes.
功能分析
Type: OpenClaw Skill Name: llm-coding-guidelines Version: 1.0.0 The skill bundle contains purely instructional guidelines (SKILL.md) designed to improve the quality and restraint of LLM-generated code. It promotes best practices such as minimal code changes, avoiding over-engineering, and explicit reasoning, with no executable code, network requests, or malicious prompt injection patterns identified.
能力评估
Purpose & Capability
The stated purpose is to guide LLM coding behavior toward simpler, more careful changes, and the SKILL.md content matches that purpose.
Instruction Scope
The instructions focus on planning, asking clarifying questions, limiting code changes, and verifying work; they do not redirect user goals or require unsafe tool use.
Install Mechanism
There is no install spec and no code files; this is an instruction-only skill.
Credentials
The skill requests no environment variables, binaries, credentials, local file indexing, or network access.
Persistence & Privilege
No persistence, background behavior, privileged access, or stored memory behavior is described.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install llm-coding-guidelines
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /llm-coding-guidelines 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release: Think before coding, simplicity first, surgical changes, goal-driven execution, and tradeoff awareness.
元数据
Slug llm-coding-guidelines
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

LLM Coding Guidelines 是什么?

Behavioral guidelines for LLM-based coding agents to reduce common mistakes. Use when writing, editing, or reviewing code to ensure surgical precision, minim... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 43 次。

如何安装 LLM Coding Guidelines?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install llm-coding-guidelines」即可一键安装,无需额外配置。

LLM Coding Guidelines 是免费的吗?

是的,LLM Coding Guidelines 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

LLM Coding Guidelines 支持哪些平台?

LLM Coding Guidelines 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 LLM Coding Guidelines?

由 hormaz(@qomg)开发并维护,当前版本 v1.0.0。

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