应用简介
迭代改进Claude代码技能,使用技能审查代理直到达到质量标准。用于改进存在多个质量问题的技能、迭代新技能直到达到标准,或使用自动修复审查周期代替手动编辑。
---
name: skill-improver
description: "Iteratively improve a Claude Code skill using the skill-reviewer agent until it meets quality standards. Use when improving a skill with multiple quality issues, iterating on a new skill until it meets standards, or automated fix-review cycles instead of manual editing."
risk: unknown
source: community
---
# Skill Improvement Methodology
Iteratively improve a Claude Code skill using the skill-reviewer agent until it meets quality standards.
## Prerequisites
Requires the `plugin-dev` plugin which provides the `skill-reviewer` agent.
Verify it's enabled: run `/plugins` — `plugin-dev` should appear in the list. If missing, install from the Trail of Bits plugin repository.
## Core Loop
1. **Review** - Call skill-reviewer on the target skill
2. **Categorize** - Parse issues by severity
3. **Fix** - Address critical and major issues
4. **Evaluate** - Check minor issues for validity before fixing
5. **Repeat** - Continue until quality bar is met
## When to Use
- Improving a skill with multiple quality issues
- Iterating on a new skill until it meets standards
- Automated fix-review cycles instead of manual editing
- Consistent quality enforcement across skills
## When NOT to Use
- **One-time review**: Use `/skill-reviewer` directly instead
- **Quick single fixes**: Edit the file directly
- **Non-skill files**: Only works on SKILL.md files
- **Experimental skills**: Manual iteration gives more control during exploration
## Issue Categorization
### Critical Issues (MUST fix immediately)
These block skill loading or cause runtime failures:
- Missing required frontmatter fields (name, description) — Claude cannot index or trigger the skill
- Invalid YAML frontmatter syntax — Parsing fails, skill won't load
- Referenced files that don't exist — Runtime errors when Claude follows links
- Broken file paths — Same as above, leads to tool failures
### Major Issues (MUST fix)
These significantly degrade skill effectiveness:
- Weak or vague trigger descriptions — Claude may not recognize when to use the skill
- Wrong writing voice (second person "you" instead of imperative) — Inconsistent with Claude's execution model
- SKILL.md exceeds 500 lines without using references/ — Overloads context, reduces comprehension
- Missing "When to Use" or "When NOT to Use" sections — Required by project quality standards
- Description doesn't specify when to trigger — Skill may never be selected
### Minor Issues (Evaluate before fixing)
These are polish items that may or may not improve the skill:
- Subjective style preferences — Reviewer may have different taste than author
- Optional enhancements — May add complexity without proportional value
- "Nice to have" improvements — Consider cost-benefit before implementing
- Formatting suggestions — Often valid but low impact
## Minor Issue Evaluation
Before implementing any minor issue fix, evaluate:
1. **Is this a genuine improvement?** - Does it add real value or just satisfy a preference?
2. **Could this be a false positive?** - Is the reviewer misunderstanding context?
3. **Would this actually help Claude use the skill?** - Focus on functional improvements
Only implement minor fixes that are clearly beneficial. Skill-reviewer may produce false positives.
## Invoking skill-reviewer
Use the skill-reviewer agent from the plugin-dev plugin. Request a review by asking Claude to:
> Review the skill at [SKILL_PATH] using the plugin-dev:skill-reviewer agent. Provide a detailed quality assessment with issues categorized by severity.
Replace `[SKILL_PATH]` with the absolute path to the skill directory (e.g., `/path/to/plugins/my-plugin/skills/my-skill`).
## Example Fix Cycle
**Iteration 1 — skill-reviewer output:**
```text
Critical: SKILL.md:1 - Missing required 'name' field in frontmatter
Major: SKILL.md:3 - Description uses second person ("you should use")
Major: Missing "When NOT to Use" section
Minor: Line 45 is verbose
```
**Fixes applied:**
- Added name field to frontmatter
- Rewrote description in third person
- Added "When NOT to Use" section
**Iteration 2 — run skill-reviewer again to verify fixes:**
```text
Minor: Line 45 is verbose
```
**Minor issue evaluation:**
Line 45 communicates effectively as-is. The verbosity provides useful context. Skip.
**All critical/major issues resolved. Output the completion marker:**
```
<skill-improvement-complete>
```
Note: The marker MUST appear in the output. Statements like "quality bar met" or "looks good" will NOT stop the loop.
## Completion Criteria
**CRITICAL**: The stop hook ONLY checks for the explicit marker below. No other signal will terminate the loop.
Output this marker when done:
```
<skill-improvement-complete>
```
**When to output the marker:**
1. **skill-reviewer reports "Pass"** or **no issues found** → output marker immediately
2. **All critical and major issues are fixed** AND you've verified the fixes → output marker
3. **Remaining issues are only minor** AND you've evaluated them as false positives or not worth fixing → output marker
**When NOT to output the marker:**
- Any critical issue remains unfixed
- Any major issue remains unfixed
- You haven't run skill-reviewer to verify your fixes worked
The marker is the ONLY way to complete the loop. Natural language like "looks good" or "quality bar met" will NOT stop the loop.
## Rationalizations to Reject
- "I'll just mark it complete and come back later" - Fix issues now
- "This minor issue seems wrong, I'll skip all of them" - Evaluate each one individually
- "The reviewer is being too strict" - The quality bar exists for a reason
- "It's good enough" - If there are major issues, it's not good enough
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
发布日期
5/16/2026
提供方
SkillOPIC
来源类型
导入
sickn33
coding
数据安全
使用 Skill 时,您的对话内容将被发送至 AI 模型进行处理。我们会严格保护您的隐私数据,不会将您的对话内容用于模型训练或分享给第三方。 以下为此 Skill 的数据处理说明。
此 Skill 将处理您的对话输入
您的消息将作为 Prompt 上下文发送至 AI 模型
所有通信均通过加密通道传输
对话记录仅保存在本地
您可以随时清除本地对话历史,清除后数据不可恢复
评分和评价
已验证评分
Skill 信息
了解此 Skill 的详细信息和功能特性
编程开发
后端开发
文件结构
SKILL.md5.9 KB
版本历史
- 公开
- 来源于用户导入
如需详细了解相关要求,请访问帮助中心,或给我们提交反馈信息