Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · AI
skill-optimizer
Analyzes AI conversation logs to evaluate skill performance and generate optimization suggestions. Use when user mentions "优化技能", "迭代技能", "skill optimization...
skill openclawclawhub Free
Analyzes AI conversation logs to evaluate skill performance and generate optimization suggestions. Use when user mentions "优化技能", "迭代技能", "skill optimization...
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- rampagepeter
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Overview
通过分析用户与 AI 的真实对话记录，对比技能的设计意图与实际表现，结合技能设计最佳实践，输出可落地的优化方案。
When to Use
用户提供了一段对话记录，想分析某个技能的实际效果 用户说"优化技能"、"迭代技能"、"分析技能表现" 用户想改进某个技能但不确定从哪里入手 不适用于： 从零创建新技能 与技能无关的对话分析
Phase 1: 收集输入
获取对话内容：用户直接粘贴文本，或提供文件路径（读取文件） 确定目标技能： 用户明确告知 → 直接使用 用户未告知 → 从对话内容中推断技能名称，向用户确认 读取目标技能的 SKILL.md 原始文档
Phase 2: 分析
从以下维度对比分析： 2.1 触发与意图匹配 技能是否在正确的场景被触发 description 中的触发词是否覆盖了实际使用场景 是否存在误触发或漏触发 2.2 流程执行 SKILL.md 中定义的工作流是否被完整执行 哪些步骤被跳过、乱序或重复 流程中是否有冗余或缺失的环节 2.3 输出质量 实际输出是否符合技能设计的预期格式和内容 输出是否对用户有实际帮助 是否存在信息过多或过少的问题 2.4 交互体验 与用户的交互是否流畅自然 是否在该问的时候问了、不该问的时候没问 引导用户的方式是否清晰 2.5 指令有效性 SKILL.md 中哪些指令被 AI 准确执行 哪些指令被忽略或误解 指令的表述是否足够明确
Phase 3: 输出报告
- 按以下结构输出分析报告：
- ## 技能分析报告：[技能名称]
- ### 基本信息
- 技能名称：
- 分析对话轮数：
- 技能版本：
- ### 总体评估
- 一段话概括技能的整体表现。
- ### 各维度分析
- #### 触发与意图匹配
- 现状：...
- 问题：...
- 建议：...
- #### 流程执行
- 现状：...
- 问题：...
- 建议：...
- #### 输出质量
- 现状：...
- 问题：...
- 建议：...
- #### 交互体验
- 现状：...
- 问题：...
- 建议：...
- #### 指令有效性
- 现状：...
- 问题：...
- 建议：...
- ### 优化建议汇总
- 按优先级排列的具体修改建议，每条包含：
- 1. 修改位置（SKILL.md 的哪个部分）
- 2. 当前内容
- 3. 建议修改为
- 4. 修改理由
Phase 4: 确认与执行
将报告呈现给用户 询问用户确认哪些建议需要执行 用户确认后，直接修改目标技能的 SKILL.md 修改完成后展示变更摘要
Common Mistakes
问题解决仅凭一次对话就下结论在报告中注明样本量，建议用户提供更多对话建议过于笼统每条建议必须指向 SKILL.md 的具体位置和具体改法忽略技能的设计意图先理解原始设计再评判，避免偏离技能定位一次改太多建议分批迭代，每次聚焦最关键的 2-3 个改进点
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md