| name | agents-module |
|---|---|
| description | Automation scripts and agent helpers for the Digital Brain. Use these scripts for recurring tasks, summaries, and maintenance. |
Scripts and workflows that help maintain and leverage your Digital Brain.
| Script | Purpose | Frequency |
|---|---|---|
weekly_review.py |
Generate weekly review from data | Weekly |
content_ideas.py |
Generate content ideas from knowledge | On-demand |
stale_contacts.py |
Find contacts needing outreach | Weekly |
metrics_snapshot.py |
Compile metrics for tracking | Weekly |
idea_to_draft.py |
Expand an idea into a draft | On-demand |
Scripts are in agents/scripts/. They work with your Digital Brain data and can be run by the agent when needed.
# Agent can execute scripts directly
python agents/scripts/weekly_review.py
# Or with arguments
python agents/scripts/content_ideas.py --pillar "ai_agents" --count 5Scripts output to stdout in a format the agent can process. They may also write to files when appropriate (e.g., generating a review document).
When using automation scripts:- Weekly review: Run every Sunday, outputs review template with data filled in
- Content ideas: Use when user asks for ideas, leverages knowledge base
- Stale contacts: Run weekly, surfaces relationships needing attention
- Metrics snapshot: Run weekly to append to metrics.jsonl
- Idea to draft: Use when user wants to develop a specific idea
Scripts read from Digital Brain files and output actionable results.
1. Run metrics_snapshot.py to update metrics.jsonl
2. Run stale_contacts.py to identify outreach needs
3. Run weekly_review.py to generate review document
4. Present summary to user
1. Read recent entries from knowledge/bookmarks.jsonl
2. Check content/ideas.jsonl for undeveloped ideas
3. Run content_ideas.py for fresh suggestions
4. Cross-reference with content calendar
1. Look up contact in network/contacts.jsonl
2. Pull recent interactions from network/interactions.jsonl
3. Check any pending todos involving them
4. Generate brief with context
To add new scripts:
- Create Python file in
agents/scripts/ - Follow existing patterns (read JSONL, output structured data)
- Document in this file
- Test with sample data