paiflisted

# PAIF Skill Use a packaged PAIF portrait for a clearly labeled, profile-derived simulation. Deterministically validate and score caller-supplied constraint results without claiming to reproduce a real person or evaluate unsupplied semantics. ## Core workflow 1. Read `personas/manifest.yaml` and select only an entry marked `usable`. 2. If an entry is `draft` or `quarantined`, disclose that it is unavailable instead of loading its legacy source. 3. Read the one reference matching the requested workflow. 4. Use `scripts/paif.py` or the public `paif_pipeline` API for deterministic validation and scoring. 5. Stop and disclose missing evidence whenever a result is incomplete. Never infer that a missing check passed. ## Workflow routing - To select, inspect, or validate a portrait, read `references/persona-schema.md`. - To generate a persona response or improve positive simulation guidance, read `references/generation-contract.md`. - To generate checks, score caller-supplied constraint results, merge task/result files, or interpret the Constraint Compliance Index, read `references/scoring-and-priority.md`. - To use narrative stages, modality, degradation state, sessions, or localization comparison, read `references/degradation-and-session.md`. - To evaluate a decision involving multiple personas, read `references/multi-persona-decisions.md`. ## Simulation workflow Load the selected usable portrait. Treat `anchor` and `must_avoid` as behavior constraints, and use the remainin