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。
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：
知识沉淀 > 数据堆积
每次分析后：
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
步骤1：提取语音记录
步骤2：AI深度分析（核心改进）
步骤3：自动导出到Obsidian
知识体系/个人工作模式/微信聊天记录_YYYY-MM-DD.mdAntigravity开发记录_YYYY-MM-DD.mdAlma使用记录_YYYY-MM-DD.md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
├── Antigravity开发记录_2026-01-12.md ← 编程App分析
├── Alma使用记录_2026-01-12.md ← 文档工具分析
├── 用户习惯清单.md ← 自动积累
├── 工作模式配置.md ← 自动积累
└── 偏好设置.md ← 自动积累
Launch the interactive dashboard:
/Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/start_dashboard.sh
Then visit: http://localhost:8080
Dashboard Features:
Static Framework (One-time creation)
├── analysis_dashboard.html (HTML structure, CSS, JS logic)
│ └── JavaScript: loadData() → fetch from API → renderDashboard()
└── Never regenerated, only data changes
Dynamic Service (Flask API)
├── analysis_server.py (lightweight backend)
│ ├── GET /api/data → Return all apps data
│ ├── POST /api/analyze → Trigger Python analysis
│ ├── GET /api/report/<app> → Return markdown report
│ └── GET /api/status → Real-time analysis status
└── Handles Python script execution and status polling
Data Processing (Python Scripts)
├── extract_voice_records.py (Query Typeless DB)
├── group_by_app.py (Group records by app)
├── generate_analysis_report.py (Generate structured reports)
└── analyze_voice_workflow.py (Master workflow controller)
~/Library/Application Support/Typeless/typeless.db~/Library/Application Support/alma/workspaces/temp-voice-extraction/by_app/*.json~/Library/Application Support/alma/workspaces/temp-voice-extraction/analysis_reports/Located at: templates/analysis_framework.json
Dimensions（根据App类型自动适配）：
extract_voice_records.py: Extract voice records from Typeless SQLite DBgroup_by_app.py: Group records by focused_app_name into separate JSON filesgenerate_analysis_report.py: Generate structured analysis reports (markdown)analyze_voice_workflow.py: Master workflow controller (orchestrates extraction, grouping, reporting)analysis_server.py: Flask API server for dashboardstart_dashboard.sh: One-click startup script for dashboardanalysis_report_template.md: Standardized template for analysis reportsanalysis_framework.json: Configuration for scene/stage/pattern recognitiontypeless_db_schema.md: Complete schema of Typeless.app SQLite databaseobsidian_organization_guidelines.md: Guidelines for structuring Obsidian notes (future integration)When you ask AI to "analyze voice records" or "generate analysis report", it will:
Example commands:
What AI does automatically:
# Check and start Flask server (background)
# Execute full analysis
python3 auto_analyze.py --all
# Read and display report content
You see:
If you want to use the visual dashboard:
start_dashboard.shAnalyze all apps:
python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/auto_analyze.py --all
Analyze specific app:
python3 /Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/auto_analyze.py --app Antigravity
Start dashboard only:
/Users/douba/.claude/skills/daily-ai-workflow-analyzer/scripts/start_dashboard.sh
不只是数据汇总，而是深度战略洞察
报告采用"直面本质"的分析框架，旨在：
| 对比维度 | v1.0 (旧版本) | v2.0 (深度洞察版) | |----------|--------------|------------------| | 核心目标 | 数据汇总和行为描述 | 深度洞察和战略指导 | | 分析深度 | 表面模式识别 | 认知偏见和战略盲点 | | 行动指导 | 只有正向建议 | 包含否定性指导 | | 价值产出 | SOP和规则清单 | 原则和偏好固化 | | 问题导向 | "用户做了什么" | "用户为什么这么做" | | 反馈机制 | 简单评分 | 多维度评估和反馈闭环 |
生成报告时必须满足：
Each report includes a feedback section:
This feedback is collected to iteratively refine the analysis framework and report structure.
The generated analysis reports can be synced to Obsidian vault:
Currently in MVP phase—focus on report quality and value extraction before automation.
npx skills add ttmouse/daily-ai-workflow-analyzer下载完整 Skill 目录，包含 SKILL.md 及所有相关文件
Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs.
Manage Apple Notes via the `memo` CLI on macOS (create, view, edit, delete, search, move, and export notes). Use when a user asks OpenClaw to add a note, list notes, search notes, or manage note folders.
Work with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.
Use when you need to control Slack from OpenClaw via the slack tool, including reacting to messages or pinning/unpinning items in Slack channels or DMs.
Manage Apple Reminders via remindctl CLI (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output.
Manage Trello boards, lists, and cards via the Trello REST API.
Category:productivity