Agent Skills › lawve-ai/awesome-legal-skills › skill-optimizer-lawvable

skill-optimizer-lawvable

GitHub

分析工作会话并提议技能改进。支持自动捕获学习成果、响应用户反馈或手动触发。通过检测纠正、成功及边缘案例信号，依据完整、精确、原子、稳定标准评估质量，进而优化技能指令。

skills/skill-optimizer-lawvable/SKILL.md lawve-ai/awesome-legal-skills

Trigger Scenarios

用户在技能相关会话中提出改进建议、纠正或补充使用完技能后自动捕获学习成果用户手动调用 self-improve 命令

Install

npx skills add lawve-ai/awesome-legal-skills --skill skill-optimizer-lawvable -g -y

More Options

Use without installing

npx skills use lawve-ai/awesome-legal-skills@skill-optimizer-lawvable

指定 Agent (Claude Code)

npx skills add lawve-ai/awesome-legal-skills --skill skill-optimizer-lawvable -a claude-code -g -y

安装 repo 全部 skill

npx skills add lawve-ai/awesome-legal-skills --all -g -y

预览 repo 内 skill

npx skills add lawve-ai/awesome-legal-skills --list

SKILL.md

Frontmatter

{
    "name": "skill-optimizer-lawvable",
    "metadata": {
        "author": "Malik Taiar (Lawvable)",
        "license": "AGPL-3.0",
        "version": "2026.01.07"
    },
    "description": "Guide to analyze a current work session and propose improvements to skills. Use (1) automatically after working with a skill to capture learnings, (2) when the user suggests improvements, corrections, or additions during a skill-related session, or (3) when the user manually invokes `self-improve`."
}

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 Type	Examples
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 case	User 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.

Grade	Example
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.

Grade	Example
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.

Grade	Example
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.

Grade	Example
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 Met	Action
All 4 criteria pass	Add to skill directly
Less than 4 criteria	Ask 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

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
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

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

self-improve off

Run:
```
touch ./.disabled
```
Reply: "Automatic mode disabled."

self-improve status

Check .disabled file existence and report.