Agent skill · Workflow & Productivity

daily-ai-workflow-analyzer

AI深度分析语音记录，揭示行为模式、认知偏见和战略盲点。不只是数据汇总，而是直击本质的战略洞察和否定性指导。提取可沉淀的核心原则和工作偏好，构建个人工作模式知识库。

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill daily-ai-workflow-analyzer --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 9 KB
Bundled scripts: none
Path: skills/analysis/daily-ai-workflow-analyzer/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# DailyAIWorkflowAnalyzer Skill ## 核心价值 **从语音记录中提取深度战略洞察，揭示认知偏见和行为盲点** 不只是数据汇总，而是： - 🔍 **识别行为模式** → 发现低效循环和回避策略 - 🧠 **诊断认知偏见** → 揭示系统性思维错误 - 🎯 **揭示战略盲点** → 指出用户自己意识不到的问题 - 💎 **沉淀核心知识** → 提炼值得长期保留的原则 - 🛑 **否定性指导** → 告诉你"停止做什么"比"开始做什么"更重要 ## 何时使用 - 当你想从日常语音记录（微信、编程App、文档工具等）中提取有价值的模式 - 当你希望AI记住你的工作习惯、偏好和标准 - 当你想避免重复的沟通和低效的工作流 - 当你需要将经验转化为可复用的规则和配置 ## 核心理念 **知识沉淀 > 数据堆积** 每次分析后： - ✅ 得到可直接应用的规则 - ✅ 更新个人工作模式知识库 - ✅ 让AI越来越了解你的标准 - ❌ 不再是看完就忘的冗长报告 ## 完整工作流（已优化） ### 一键分析所有应用 ```bash python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/analyze_voice_workflow.py --days 1 --all ``` ### 分析特定应用 ```bash python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/analyze_voice_workflow.py --days 1 --app Antigravity ``` ### 工作流程说明 **步骤1：提取语音记录** - 从Typeless.app数据库提取最近N天的记录 - 按应用自动分组 **步骤2：AI深度分析**（核心改进） - 识别重复出现的问题（≥2次） - 提取新发现的原则和规则 - 生成可执行的行动清单 - 分析用户习惯和工作模式 - 根据App类型适配分析维度（聊天、编程、文档等） **步骤3：自动导出到Obsidian** - 生成结构化笔记到 `知识体系/个人工作模式/` - 智能文件命名（根据App类型）： - 微信 → `微信聊天记录_YYYY-MM-DD.md` - 编程App → `Antigravity开发记录_YYYY-MM-DD.md` - 文档工具 → `Alma使用记录_YYYY-MM-DD.md` - 自动更新知识库文件： - [[用户习惯清单]] - [[工作模式配置]] - [[偏好设置]] ### 输出示例 ``` 知识体系/个人工作模式/ ├── 微信聊天记录_2026-01-12.md ← 每日分析结果

What's inside
Steps it walks through
  1. 核心价值
  2. 何时使用
  3. 核心理念
  4. 完整工作流（已优化）
  5. 一键分析所有应用
  6. 分析特定应用
  7. 工作流程说明
  8. 输出示例
  9. Phase 4: Visual Dashboard
  10. Architecture
  11. Key Configuration
  12. Paths
  13. Analysis Framework
  14. Resources
Ships with 1 file
  • metadata.json
Commands it runs
python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/analyze_voice_workflow.py --days 1 --all
python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/analyze_voice_workflow.py --days 1 --app Antigravity
Check and start Flask server (background)
Execute full analysis
python3 auto_analyze.py --all
Read and display report content
python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/auto_analyze.py --all
python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/auto_analyze.py --app Antigravity
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About this skill
What does the daily-ai-workflow-analyzer skill do?

AI深度分析语音记录，揭示行为模式、认知偏见和战略盲点。不只是数据汇总，而是直击本质的战略洞察和否定性指导。提取可沉淀的核心原则和工作偏好，构建个人工作模式知识库。

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill daily-ai-workflow-analyzer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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