Skill: openlark/agent-daily-review (version 1.0.0)

--- name: agent-daily-review description: Helps agents conduct structured end-of-day review, reflection, and documentation. Provides capabilities to scan today's records, categorize activities, perform reflective analysis, and generate review reports. Supports Cron auto-trigger for cumulative growth with each run. --- # Agent Daily Review ## Overview The Daily Review skill helps agents conduct systematic review and reflection at the end of the day, transforming fragmented daily records into structured growth accumulation. **Core Capabilities:** 1. **Scan Records** - Automatically scan today's memory files, artifacts, and MEMORY.md entries 2. **Categorize Activities** - Classify activities into: Completed, In Progress, Issues/Blockers, Learning/Growth, Others 3. **Reflect and Analyze** - Calculate productivity score, identify highlights and challenges, generate improvement suggestions 4. **Generate Report** - Output structured review report and archive to long-term memory **Use Cases:** - User says "Do my daily review for today" - User says "Summarize today" - Cron scheduled task triggers (e.g., daily at 22:00) - User wants to review work/learning status for a specific day ## Workflow ### 1. Scan Today's Records Execute `scripts/daily_review.py` to scan the following: - `memory/YYYY-MM-DD.md` - Today's journal entries - `MEMORY.md` - Today's entries in long-term memory - `workspace/*.md` - Artifact files generated today ### 2. Categorize Activities Automatically identify and categorize: - **Completed** - Contains keywords like "completed," "done," "resolved," ✅ - **In Progress** - Contains keywords like "in progress," "working on," 🔄 - **Issues/Blockers** - Contains keywords like "issue," "blocked," "bug," ❌ - **Learning/Growth** - Contains keywords like "learned," "researched," "understood" - **Meetings/Communication** - Contains keywords like "meeting," "discussed," "sync" ### 3. Reflect and Analyze Perform intelligent analysis based on categorization results: - **Productivity Score** - Calculate based on record count and artifact count (0-100) - **Today's Highlights** - Identify completed important tasks and decisions - **Challenges Encountered** - Summarize issues and pending items - **Improvement Suggestions** - Generate personalized recommendations based on data ### 4. Generate Report Output structured report containing: - Today's Overview (statistics) - Completed Tasks List - In Progress Tasks List - Issues/Blockers - Learning/Growth Records - Highlights Summary - Reflection and Suggestions - Tomorrow's Plan Framework ### 5. Archive to Memory - Save review report to `reviews/review_YYYY-MM-DD.md` - Append review summary to `MEMORY.md` ## Usage ### Manual Execution ```bash # Execute today's review python scripts/daily_review.py # Specify working directory python scripts/daily_review.py -w /path/to/workspace # Specify output file python scripts/daily_review.py -o /path/to/output.md # Review specific date python scripts/daily_review.py -d 2024-01-15 # Do not save to MEMORY.md python scripts/daily_review.py --no-memory ``` ### Use as Module ```python from scripts.daily_review import DailyReview review = DailyReview("/path/to/workspace") report = review.run(save_to_memory=True) print(report) ``` ### Cron Auto-Trigger Set up automatic daily review at 22:00: ```bash # Add scheduled task using openclaw cron openclaw cron add --name "daily-review" \ --schedule "0 22 * * *" \ --command "python ~/.qclaw/skills/daily-review/scripts/daily_review.py" ``` Or using cron tool: ```json { "name": "daily-review", "schedule": {"kind": "cron", "expr": "0 22 * * *", "tz": "Asia/Shanghai"}, "payload": { "kind": "agentTurn", "message": "Please perform today's review using the daily-review skill, scanning today's records and generating a review report." }, "sessionTarget": "isolated" } ``` ## Report Format Review reports use Markdown format with the following sections: ```markdown # Daily Review Report - YYYY-MM-DD ## 📊 Today's Overview - Date, Record Count, Artifact Count, Productivity Score ## ✅ Completed - Task List ## 🔄 In Progress - Pending List ## ⚠️ Issues/Blockers - Issue List ## 📚 Learning/Growth - Learning Records ## 🎯 Today's Highlights - Highlights Summary ## 💭 Reflection and Suggestions - Improvement Suggestions ## 📝 Tomorrow's Plan - Plan Framework ``` ## Directory Structure ``` workspace/ ├── memory/ │ └── 2024-01-15.md # Today's journal entries ├── reviews/ │ └── review_2024-01-15.md # Review report ├── MEMORY.md # Long-term memory (review summary appended here) └── *.md # Artifacts generated today ``` ## Tips 1. **Cultivate Journaling Habit** - Record timestamped entries in `memory/YYYY-MM-DD.md` daily for better review results 2. **Use Keywords** - Use keywords like "completed," "learning," "encountered issue" when journaling to facilitate auto-categorization 3. **Periodic Review** - Review weekly/monthly review reports to discover growth trajectory 4. **Integrate with Cron** - Set up automatic review to ensure daily reflection is never missed ## Resources - `scripts/daily_review.py` - Core review script - `references/framework.md` - Detailed review framework explanation (optional reading)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)