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Define and load execution-profile.yaml — the per-project Layer-3 file that declares which personas a project instantiates and how stages route. It is distinct from project.yaml (human-authored config, #4) and has a different change cadence: regenerated on structural change, not hand-edited (Spec §17.5).
A Pydantic schema for execution-profile.yaml declaring, per Spec §17.5: the instantiated personas (type × speciality list); per-stage executor confirmation where it differs from default (AI persona vs engine); routing (which persona handles which repo/role; which QA specialities apply); any project-specific skill overrides/additions.
A fail-fast loader validating the profile at startup, consistent with the project.yaml loader pattern (project.yaml Pydantic schema and fail-fast loader #4) — a malformed profile errors before any wave begins.
The schema models both Spec §17.5 example shapes: the Trive multi-persona shape (backend/frontend/admin + accessibility/responsiveness/ui-ux QA) and the backend-only shape (planner, implementor×backend, reviewer×backend, reviewer×security, no UI QA).
Define and load
execution-profile.yaml— the per-project Layer-3 file that declares which personas a project instantiates and how stages route. It is distinct fromproject.yaml(human-authored config, #4) and has a different change cadence: regenerated on structural change, not hand-edited (Spec §17.5).Spec §17.5 (Layer 3 — project execution profile), §17.2 (three-layer overview).
Acceptance criteria
execution-profile.yamldeclaring, per Spec §17.5: the instantiated personas (type × specialitylist); per-stage executor confirmation where it differs from default (AI persona vs engine); routing (which persona handles which repo/role; which QA specialities apply); any project-specific skill overrides/additions.project.yamlloader pattern (project.yaml Pydantic schema and fail-fast loader #4) — a malformed profile errors before any wave begins.type×specialityentries are valid against the fixed type set and known specialities; skill-override ids resolve against the canonical set (Canonical skill model and loader (metadata + body; tool-base + per-project) #19).Notes
This issue is the schema + loader only. Generation of the profile by the tech-lead session is #23; consumption by the renderer is #22.
Depends on: #1, #4