What problem does it solve?
This Skill helps maintain high-signal identity records for people and products so future AI analysis can understand context more accurately. It prevents bloated archives, repeated meeting notes, and weak personality or product inferences by enforcing evidence thresholds, update rules, and clear ownership of information.
Core Features & Use Cases
- Structured profiling for people: Maintains person profiles across five dimensions: identity and role, priorities and agenda, decision patterns, strengths and blind spots, and leverage relative to the user.
- Structured profiling for products: Maintains product profiles across four dimensions with explicit entry thresholds, strategic decisions, architecture context, and refreshed current status.
- Evidence-based inference rules: Separates facts from patterns, requires triple validation before writing behavioral conclusions, and records observation boundaries where inference is not reliable.
- Merge-first maintenance: Updates existing dimensions directly instead of appending dated notes, making profiles concise, current, and authoritative.
- Use cases: Use it when updating identity/ records after meetings, consolidating repeated mentions of stakeholders, deciding whether a product deserves its own profile, or linking journals to the correct source of truth.
Quick Start
Before updating any file under identity/, ask the AI to load the identity-profiling skill and merge the latest meeting evidence into the correct person or product profile using its dimension and validation rules.
