davekilleen Identity Snapshot
Reads existing Dex data and synthesizes System/identity-model.md — a living document the system writes, not the user. This captures who you are as a professional based on your actual behavior, not self-reported traits.
When to Run
- Manually via
/identity-snapshot - Auto-triggered during
/week-review(append identity model update to review workflow)
Data Sources
Read ALL of the following in parallel before synthesizing:
- Quarter Goals —
01-Quarter_Goals/Quarter_Goals.md- What you're working toward, pillar distribution, ambition level
- Week Priorities —
02-Week_Priorities/Week_Priorities.md- Recent 4 weeks of priorities (look for patterns in what gets prioritized)
- Tasks —
03-Tasks/Tasks.md- Completion patterns, pillar distribution, velocity, what gets blocked
- Session Learnings —
System/Session_Learnings/*.md(last 30 days)- What you've learned, recurring themes
- Mistake Patterns —
06-Resources/Learnings/Mistake_Patterns.md- Known failure modes, triggers, what to watch for
- Skill Ratings —
System/Skill_Ratings/ratings.jsonl- Which skills score highest, what you value in AI interactions
- User Profile —
System/user-profile.yaml- Existing identity data, communication preferences
Synthesis
Write to System/identity-model.md with this structure:
# Identity Model
*Auto-generated by Dex — last updated YYYY-MM-DD*
## Working Patterns
- Pillar balance: [distribution across pillars]
- Priority cadence: [how often priorities shift, what stays stable]
- Task velocity: [completion rate, average items per week]
- Peak focus areas: [what dominates recent weeks]
## Decision Tendencies
- Under pressure: [what gets prioritized vs deprioritized]
- Goal selection: [ambitious vs tactical, how goals evolve]
- Time allocation: [deep work vs meetings vs quick tasks]
## Quality Preferences
- Highest-rated skills: [from ratings.jsonl]
- What "good" looks like: [patterns from high ratings + notes]
- What frustrates: [patterns from low ratings + mistake patterns]
## Growth Areas
- Recurring gaps: [from mistake patterns, things that keep coming up]
- Skills under development: [from learnings, new capabilities being adopted]
- Blind spots: [pillars or areas consistently neglected]
## Communication Style
- Formality: [from profile + observed patterns]
- Decision speed: [fast/deliberate based on task patterns]
- Feedback preference: [from profile]
Rules
- Never ask the user for input. This is purely observational.
- Be specific. Use actual data points, not generic statements.
- Be honest. If a pillar is neglected, say so. If velocity dropped, note it.
- Date-stamp every generation. The model should show evolution over time.
- If any data source is missing or empty, note it as "[No data available]" and move on.