| name | digital-brain |
| description | This skill should be used for personal operating-system workflows: content creation, voice consistency, relationship lookup, meeting preparation, weekly review, goal tracking, personal brand management, and network management. |
| version | 1.0.0 |
Digital Brain
A structured personal operating system for managing digital presence, knowledge, relationships, and goals with AI assistance. Designed for founders building in public, content creators growing their audience, and tech-savvy professionals seeking AI-assisted personal management.
Important: This skill uses progressive disclosure. Module-specific instructions are in each subdirectory's .md file. Only load what's needed for the current task.
When to Activate
Activate this skill when the user:
- Requests content creation (posts, threads, newsletters) - load identity/voice.md first
- Asks for help with personal brand or positioning
- Needs to look up or manage contacts/relationships
- Wants to capture or develop content ideas
- Requests meeting preparation or follow-up
- Asks for weekly reviews or goal tracking
- Needs to save or retrieve bookmarked resources
- Wants to organize research or learning materials
Trigger phrases: "write a post", "my voice", "content ideas", "who is [name]", "prepare for meeting", "weekly review", "save this", "my goals"
Core Concepts
Progressive Disclosure Architecture
The Digital Brain follows a three-level loading pattern:
| Level | When Loaded | Content |
|---|
| L1: Metadata | Always | This SKILL.md overview |
| L2: Module Instructions | On-demand | [module]/[MODULE].md files |
| L3: Data Files | As-needed | .jsonl, .yaml, .md data |
File Format Strategy
Formats chosen for optimal agent parsing:
- JSONL (
.jsonl): Append-only logs - ideas, posts, contacts, interactions
- YAML (
.yaml): Structured configs - goals, values, circles
- Markdown (
.md): Narrative content - voice, brand, calendar, todos
- XML (
.xml): Complex prompts - content generation templates
Append-Only Data Integrity
JSONL files are append-only. Never delete entries:
- Mark as
"status": "archived" instead of deleting
- Preserves history for pattern analysis
- Enables "what worked" retrospectives
Detailed Topics
Module Overview
digital-brain/
├── identity/ → Voice, brand, values (READ FIRST for content)
├── content/ → Ideas, drafts, posts, calendar
├── knowledge/ → Bookmarks, research, learning
├── network/ → Contacts, interactions, intros
├── operations/ → Todos, goals, meetings, metrics
└── agents/ → Automation scripts
Identity Module (Critical for Content)
Always read identity/voice.md before generating any content.
Contains:
voice.md - Tone, style, vocabulary, patternsbrand.md - Positioning, audience, content pillarsvalues.yaml - Core beliefs and principlesbio-variants.md - Platform-specific biosprompts/ - Reusable generation templates
Content Module
Pipeline: ideas.jsonl → drafts/ → posts.jsonl
- Capture ideas immediately to
ideas.jsonl
- Develop in
drafts/ using templates/
- Log published content to
posts.jsonl with metrics
- Plan in
calendar.md
Network Module
Personal CRM with relationship tiers:
inner - Weekly touchpointsactive - Bi-weekly touchpointsnetwork - Monthly touchpointsdormant - Quarterly reactivation checks
Operations Module
Productivity system with priority levels:
- P0: Do today, blocking
- P1: This week, important
- P2: This month, valuable
- P3: Backlog, nice to have
Practical Guidance
Content Creation Workflow
1. Read identity/voice.md (REQUIRED)
2. Check identity/brand.md for topic alignment
3. Reference content/posts.jsonl for successful patterns
4. Use content/templates/ as starting structure
5. Draft matching voice attributes
6. Log to posts.jsonl after publishing
Pre-Meeting Preparation
1. Look up contact: network/contacts.jsonl
2. Get history: network/interactions.jsonl
3. Check pending: operations/todos.md
4. Generate brief with context
Weekly Review Process
1. Run: python agents/scripts/weekly_review.py
2. Review metrics in operations/metrics.jsonl
3. Check stale contacts: agents/scripts/stale_contacts.py
4. Update goals progress in operations/goals.yaml
5. Plan next week in content/calendar.md
Examples
Example: Writing an X Post
Input: "Help me write a post about AI agents"
Process:
- Read
identity/voice.md → Extract voice attributes
- Check
identity/brand.md → Confirm "ai_agents" is a content pillar
- Reference
content/posts.jsonl → Find similar successful posts
- Draft post matching voice patterns
- Suggest adding to
content/ideas.jsonl if not publishing immediately
Output: Post draft in user's authentic voice with platform-appropriate format.
Example: Contact Lookup
Input: "Prepare me for my call with Sarah Chen"
Process:
- Search
network/contacts.jsonl for "Sarah Chen"
- Get recent entries from
network/interactions.jsonl
- Check
operations/todos.md for pending items with Sarah
- Compile brief: role, context, last discussed, follow-ups
Output: Pre-meeting brief with relationship context.
Guidelines
- Voice First: Always read
identity/voice.md before any content generation
- Append Only: Never delete from JSONL files - archive instead
- Update Timestamps: Set
updated field when modifying tracked data
- Cross-Reference: Knowledge informs content, network informs operations
- Log Interactions: Always log meetings/calls to
interactions.jsonl
- Preserve History: Past content in
posts.jsonl informs future performance
Integration
This skill integrates context engineering principles:
- context-fundamentals - Progressive disclosure, attention budget management
- memory-systems - JSONL for persistent memory, structured recall
- tool-design - Scripts in
agents/scripts/ follow tool design principles
- context-optimization - Module separation prevents context bloat
References
Internal references:
External resources:
Skill Metadata
Created: 2024-12-29
Last Updated: 2024-12-29
Author: Murat Can Koylan
Version: 1.0.0
