Token导航 LogoToken导航TokenDH.com
研究检索只读github未标认证来源可访问许可证需确认审计异常

skill-optimizer-lawvable技能优化器 lawvable

Agent Skill

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。

总安装

897

周安装

37

GitHub Stars

302

下载量

293
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills