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Agent Skill · 研究检索

skill-optimizer-lawvable(技能优化器 lawvable)

skill-optimizer-lawvable 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

skill-optimizer-lawvable 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 44,713。

总安装 897周安装 37GitHub Stars 302下载 293核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:skill-optimizer-lawvable(技能优化器 lawvable)
来源仓库:https://github.com/lawvable/awesome-legal-skills
仓库路径:skills/skill-optimizer-lawvable
安装命令:
npx skills add https://github.com/lawvable/awesome-legal-skills --skill skill-optimizer-lawvable
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/lawvable/awesome-legal-skills --skill skill-optimizer-lawvable

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

skill-optimizer-lawvable 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。

安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。安装方式:github,使用 npx skills add 命令添加。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/skill-optimizer-lawvable

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/lawvable/awesome-legal-skills --skill skill-op…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

skill-optimizer-lawvable 怎么安装?

在终端执行 npx skills add https://github.com/lawvable/awesome-legal-skills --skill skill-optimizer-la…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skill-optimizer-lawvable 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

skill-optimizer-lawvable 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

skill-optimizer-lawvable 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

skill-optimizer-lawvable 用的人多吗?

公开数据是累计安装 897 次,近一周安装 37 次,下载 293 次,GitHub 302 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

skill-optimizer-lawvable 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
skill-optimizer-lawvable

技能优化器 lawvable · 本页

897302只读未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Self-Improve Skill

Analyze the current conversation and propose improvements to skills based on corrections, successes, and edge cases discovered during the work session.

Triggers

  • self-improve - Analyze session and propose improvements
  • self-improve [skill-name] - Target a specific skill
  • self-improve on - Enable automatic mode (hook)
  • self-improve off - Disable automatic mode
  • self-improve status - Show automatic mode status
  • self-improve [skill-name] history - Show modification history

Main Workflow (self-improve)

Step 1: Identify the Skill

If skill name not provided, list available skills from skills/ directory and ask:

Which skill should I analyze for this session?
[List skills found in skills/ directory]

Step 2: Detect Signals

Scan the conversation for signals - moments where the user expressed feedback:

Signal TypeExamples
Correction"No", "That's not right", "It's missing X", "Always do Y", user rewrites output
Success"Perfect", "Yes", "Exactly", user accepts without changes
Edge caseUser needed a workaround, skill couldn't handle the request

Step 3: Evaluate Each Signal for Quality

For each correction signal, evaluate if it can become a good skill instruction.

Quality Criteria

1. COMPLETE

The instruction includes all information needed to apply it. No need to look elsewhere or make assumptions.

GradeExample
Pass"Structure output as: Key Terms / Risk Areas / Suggested Revisions"
Fail"Use the standard format" (which format?)
Fail"Follow our firm's guidelines" (what guidelines?)

2. PRECISE

No vague or subjective terms. Two different people reading the instruction would understand it the same way.

GradeExample
Pass"Flag non-compete clauses over 12 months as high risk"
Fail"Be more thorough in the analysis"
Fail"Make it more appropriate for clients"

3. ATOMIC

One instruction addresses one single requirement. Multiple checks should be split into separate instructions.

GradeExample
Pass"Check for governing law clause"
Fail"Check for governing law, jurisdiction, and arbitration clauses" (three checks - split them)

4. STABLE

If referencing regulations or standards, specify the version or date. The instruction should be evaluable the same way regardless of when it's read.

GradeExample
Pass"Review the termination provisions under our internal policy [policy name and reference], dated December 12, 2024."
Fail"Follow latest market standards" (which standards? will change over time)

Step 4: Grade the Signal

Criteria MetAction
All 4 criteria passAdd to skill directly
Less than 4 criteriaAsk for clarification (see Step 5)

Step 5: Ask for Clarification

When feedback doesn't meet all criteria, ask for what's missing using the AskUserQuestion tool:

I detected a correction but need more information to improve the skill.

You said: "[user's feedback]"

To create a clearer instruction, I need the following information:

[Structured tool call listing what's missing based on failed criteria]

If the user provides clarification → Update the instruction and proceed to Step 6.

If the user prefers the original → Proceed to Step 6 with the original instruction.

Step 6: Propose Changes

--- Learning: [skill-name] ---

Proposed additions:

1. "[exact instruction to add]"
   Source: "[quote from conversation]"

2. "[exact instruction to add]"
   Source: "[quote from conversation]"

---

Apply these changes? [Y/n]

Step 7: If Approved

  1. Update SKILL.md

- Read skills/[skill-name]/SKILL.md - Add each instruction in the appropriate section - Each instruction must be readable and applicable on its own

  1. Update skills/[skill-name]/CHANGELOG.md

- Create if doesn't exist - Add new entry AT THE TOP: ## [DATE (format: "January 7, 2026")] [Description of changes in natural language, 1-3 sentences] - Entry rules: - Most recent at top - 1-3 sentences max - Natural language - No git references

Step 8: Save Observations

For signals that couldn't be processed, offer to save:

Save these observations for later review?
- "[signal 1]" - Status: [why insufficient]
- "[signal 2]" - Status: [why insufficient]

If yes, append to skills/[skill-name]/OBSERVATIONS.md


Secondary Commands

self-improve on

  1. Run: rm -f./.disabled
  2. Reply: "Automatic mode enabled."

self-improve off

  1. Run: touch./.disabled
  2. Reply: "Automatic mode disabled."

self-improve status

Check .disabled file existence and report.

self-improve [skill-name] history

  1. Display CHANGELOG.md content
  2. Ask: "Would you like to revert to a previous version?"
  3. If yes:

- update the appropriate sections in skills/[skill-name]/SKILL.md - update skills/[skill-name]/CHANGELOG.md with a rollback note


Examples

Example 1: All criteria met

User said: "Always flag non-compete clauses over 12 months as high risk"

Evaluation:

  • Complete: Yes - instruction is fully specified
  • Precise: Yes - "12 months" and "high risk" are clear
  • Atomic: Yes - single check
  • Stable: Yes - no time dependency

Result: Add directly

Example 2: Missing criteria

User said: "Flag any non-market-standard indemnification clause"

Evaluation:

  • Complete: No - "non-market-standard" is not defined
  • Precise: No - "market standard" is subjective and varies by deal type
  • Atomic: Yes - single check
  • Stable: No - market standards evolve over time

Action: Ask for clarification using the AskUserQuestion tool:

I detected a correction but need more details.

You said: "Flag any non-market-standard indemnification clause"

To make this actionable, can you specify:
- What makes an indemnification clause "non-market-standard"? (e.g., uncapped liability, coverage of indirect damages, no carve-outs for gross negligence)

Do you want to provide more details, or should I add the instruction as you stated it?

If user clarifies: Update the instruction and add it. If user prefers the original: Add the instruction as stated.


Important Notes

  • Never guess what the user meant - always ask if unclear
  • Never infer requirements from context - they must be explicit
  • One instruction = one check - split bundled feedback
  • Fewer good instructions is better than many vague ones
  • CHANGELOG.md is the user-facing record

平台分布

Codex

38%
按下载量换算111

Claude

28.14%
按下载量换算82

Cursor

19.78%
按下载量换算58

Gemini CLI

9.28%
按下载量换算27

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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