Daily Review

by openclaw

skill

Comprehensive daily performance review with communication tracking, meeting analysis, output metrics, and focus time monitoring. Your AI performance coach.

Skill Details

Repository Files

3 files in this skill directory


name: daily-review version: 1.0.0 description: Comprehensive daily performance review with communication tracking, meeting analysis, output metrics, and focus time monitoring. Your AI performance coach. author: henrino3 tags: [productivity, performance, tracking, review, coach]

Daily Review Skill

Generate comprehensive daily performance reviews with AI coaching insights.

Features

Feature Source Status
Emails sent Gmail API
Slack messages Slack API
X.com mentions Bird CLI
Meetings attended Fireflies (speaker verified)
Git commits git log
Docs modified Google Drive API
Screen Time macOS knowledgeC.db
ActivityWatch AW API

Usage

# Run daily review for today
~/clawd/skills/daily-review/scripts/daily-review.sh

# Run for specific date
~/clawd/skills/daily-review/scripts/daily-review.sh 2026-01-15

Sample Output

🏆 Daily Performance Review - 2026-01-15
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

📬 COMMUNICATION
  • Emails sent: 6
  • Slack messages: 203
  • X.com mentions: 5

📅 MEETINGS (Fireflies - speaker verified)
  • CEO Chat (70 min)
  • Meeting with Perfectos (27 min)
  • US Squad Standup (27 min)
  Total: 3 meetings (~2.0 hrs)

💻 OUTPUT
  • Git commits: 6
  • Docs modified: 20
  • Messages to Ada: 73

⏱️ FOCUS TIME
  Screen Time: 9.7 hrs
  • Atlas: 203min
  • Slack: 163min
  • Telegram: 45min
  
  ActivityWatch: 8.5 hrs
  • Telegram: 120min
  • Ghostty: 90min
  • Chrome: 45min

Requirements

APIs & Services

  • Gmail: Google Workspace service account or gog OAuth
  • Slack: Slack API token (user_token for search)
  • Fireflies: API key for meeting transcripts
  • Google Drive: Service account for docs tracking

Tools

  • Bird CLI: For X.com/Twitter (requires auth_token + ct0 cookies)
  • ActivityWatch: Local app tracking (http://localhost:5600)

macOS (for Screen Time)

  • SSH access to Mac
  • get_screentime.py script for knowledgeC.db queries

Installation

  1. Copy skill to your clawd workspace:
cp -r daily-review ~/clawd/skills/
  1. Install dependencies:
# Bird CLI (on Mac)
cd ~/Code && git clone https://github.com/steipete/bird.git
cd bird && npm install && npm run build:dist

# ActivityWatch
# Download from https://activitywatch.net/
  1. Configure secrets:
# Bird (X.com)
cat > ~/clawd/secrets/bird.env << 'EOF'
AUTH_TOKEN=your_auth_token
CT0=your_ct0
EOF

# Fireflies
echo "your_api_key" > ~/clawd/secrets/fireflies.key

# Slack
echo '{"user_token": "xoxp-xxx"}' > ~/clawd/secrets/slack-super-ada.json
  1. Add cron job for daily 09:00 review:
clawdbot cron add --name "daily-review" --schedule "0 9 * * *"

Screen Time Query

The skill queries macOS Screen Time directly from knowledgeC.db:

SELECT 
  ZVALUESTRING as app,
  SUM(ZENDDATE - ZSTARTDATE) as seconds
FROM ZOBJECT 
WHERE ZSTREAMNAME = '/app/usage' 
AND date(ZSTARTDATE + 978307200, 'unixepoch') = '2026-01-15'
GROUP BY ZVALUESTRING
ORDER BY seconds DESC

Fireflies Speaker Verification

Meetings are verified by checking if user actually spoke (not just invited):

{
  transcripts(limit: 30) {
    title dateString duration
    sentences { speaker_name }
  }
}

Only meetings where speaker_name contains user's name are counted.

License

MIT

Related Skills

Attack Tree Construction

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

skill

Grafana Dashboards

Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.

skill

Matplotlib

Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.

skill

Scientific Visualization

Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.

skill

Seaborn

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

skill

Shap

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model

skill

Pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

skill

Query Writing

For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations

skill

Pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

skill

Scientific Visualization

Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.

skill

Skill Information

Category:Skill
Version:1.0.0
Last Updated:1/16/2026