# so-run-operations - Local Execution Policy and Upstream Handoff This local reference preserves the digitaltwin workflow milestone. Scene Optimizer mechanics for this step are owned by upstream `usd-optimize`. - Public repository: [https://github.com/NVIDIA-omniverse/usd-optimize/](https://github.com/NVIDIA-omniverse/usd-optimize/) - Package path: `.agents/skills/run-operations/SKILL.md` - Upstream web URL: [https://github.com/NVIDIA-omniverse/usd-optimize/blob/main/.agents/skills/run-operations/SKILL.md](https://github.com/NVIDIA-omniverse/usd-optimize/blob/main/.agents/skills/run-operations/SKILL.md) Resolve the upstream guide without cloning the source repo: 1. `$SCENE_OPTIMIZER_PACKAGE_ROOT/.agents/skills/run-operations/SKILL.md` 2. `$SO_HOME/.agents/skills/run-operations/SKILL.md` If no package root is available, download and extract the published `scene_optimizer_core_...release.zip` package for the target platform (direct archive URLs are in `references/upstreams/usd-optimize.md`), or use the package path/URL supplied by the user. If the user supplies an extracted package root directly, resolve this same package path under that root. If GitHub raw fetch is available, the web URL above is acceptable for docs-only reads. Do not clone the source repo just to read upstream SO guidance. ## Local Responsibilities - Run the session runtime gate from `setup-usd-performance-tuning/references/runtime-context-header.md` and consume `/setup-preflight.json`. - Cross-check every planned op key against `sceneOptimizer.operationsAvailable`; block with `blocked_missing_scene_optimizer` or `blocked_missing_so_operation` when required. - Apply local output workspace policy and `runtime-artifact-token-budget.md`; keep logs on disk and read bounded summaries only. - Apply destructive-operation approval gates via `references/operation-safety.md` before mutation. - Keep digitaltwin evidence-to-config routing in `references/config-from-evidence.md`. - Treat `references/invocation.md` as the only local source of truth for Python/API invocation shapes. - For Phase 4b multi-target optimization, use `references/batch-mode.md` for target enumeration, adaptive concurrency, prototype-first ordering, hash-based output names, resource observations, and remainder-script prompts. - Preserve logical milestone name `so-run-operations` and hand results to profile/compare/report phases. ## Pre-flight Checklist Before executing the op chain, re-read and confirm: - [ ] `references/operation-safety.md` — parameter prerequisites gate, confirmation prompt format, destructive-op approval policy. - [ ] Every op key cross-checked against `setup-preflight.json` `sceneOptimizer.operationsAvailable`. - [ ] Per-op `parameter_prerequisites` frontmatter read for each destructive op. - [ ] `references/units-and-tolerances.md` — conversion formula for any tolerance-based op. - [ ] `references/invocation.md` for local invocation mechanics and upstream handoff. - [ ] `references/batch-mode.md` for multi-target orchestration. - [ ] `runtime-artifact-token-budget.md` §"Stderr Production Guard" — redirect subprocess stderr, cap at 50 MB, retain head/tail samples. ## Execution Handoff Use `references/invocation.md` for supported Python/API invocation shapes, optional helper wrappers, selected-runtime API probing, output saving, and generic failure handling. Use this local file only for digitaltwin workflow gating, batch orchestration policy, and reporting policy.