Run phased context interview workflows
srcskillsetup L2★13,726
danielmiessler/Personal_AI_Infrastructure ↗What it does
Run phased conversational context interviews
Best for
Quarterly context maintenance where Phase 1 (MISSION, GOALS, PROBLEMS) gets review-and-refine even if nothing seems outdated—prevents context drift.
Inputs
- · PAI context files (TELOS, IDEAL_STATE, preferences, identity)
- · prior session history
- · user responses to targeted review questions
Outputs
- · updated TELOS files (MISSION, GOALS, PROBLEMS, STRATEGIES, etc.)
- · IDEAL_STATE dimension updates (HEALTH, MONEY, FREEDOM, RELATIONSHIPS, CREATIVE)
- · preferences inventory (BOOKS, BANDS, RESTAURANTS, LEARNING)
- · timestamped archive of changes
Requires
- · InterviewScan.ts script (phase scoring)
- · Edit tool (file updates)
- · Voice notification (optional curl to localhost:31337)
Preconditions
- · PAI context files exist (even if sparse)
- · Phase 1 (TELOS) prioritized in review
- · Voice/input channel available for responses
Failure modes
- · Skipping Phase 1 foundational files → misses core updates
- · Review mode on sparse files → low quality refinement
- · Not walking through file-by-file → surface-level results
- · Treating RHYTHMS (Phase 9) as priority → dilutes foundational work
Trust signals
- · Phased interview model (Phase 1 always first, regardless of completeness)
- · Completeness-based mode selection (80%+ = review, <80% = fill)
- · File-by-file priority ordering derived from leverage
- · InterviewScan.ts script integration for automated phase scoring