content-workflow-cli

name	content-workflow-cli
description	Use when the user wants the public batch shortcut for a prepared agentic asset workflow, including single-asset material assignment and three-phase large-scene execution or resume through content-workflow-cli.

content-workflow-cli

Use this skill when the user wants the batch shortcut for a prepared agentic asset workflow.

content-workflow-cli is a launcher. It is not the source of truth for Workbench API mechanics or workflow methodology.

Current Primary Workflow

content-workflow-cli materials assign \
  --usd path/to/asset.usdc \
  --reference-image path/to/reference.png \
  --additional-instructions-file path/to/material-guidance.md \
  --optimizer-selection agent \
  --materials-yaml path/to/materials.yaml \
  --output-dir agentic/runs/example

Use --optimizer-selection agent when optimizer behavior should be chosen from the asset rather than fixed by the launcher. The wrapper first provides an unoptimized Workbench inspection to the child agent, validates the resulting raw/optimizer_decision.json, and only then creates the material-authoring session with the selected optimization, prototype flattening, deinstancing, splitting, and deduplication settings. Fixed optimizer flags remain available for reproducible diagnostics and explicit user overrides, but do not combine them with agent selection.

Optimizer decisions are task-scoped. materials assign selects settings against visible material coverage, independent appearance authoring, and source-path mapping. physics apply runs a separate unoptimized inspection and selects settings against component membership, rigid-body and joint topology, collider/helper roles, legal authoring targets, and runtime behavior. Each optimizer_decision.json declares task; the wrapper rejects a decision for a different operation.

Use --additional-instructions for short inline guidance or --additional-instructions-file for durable multi-line policy. The wrapper stores the normalized text in request.json, includes it in the child-agent task, and reuses it during bounded VQA refinement. Provide task-wide guidance once; do not generate per-prim prompt copies.

Large-Scene Workflow

Use the public scene launcher rather than invoking the internal transition tool or agent runtime directly:

content-workflow-cli scene run \
  --usd path/to/scene.usd \
  --task material \
  --materials-yaml path/to/materials.yaml \
  --reference-dir path/to/references \
  --reference-image path/to/accepted-render.png \
  --additional-instructions-file path/to/material-guidance.md

The wrapper writes a resolved request and large_scene_run.json, launches one long-running agent from the isolated agentic/ workspace, and returns success only after decomposition, asset-task processing, and collection complete their handoff gates. Resume a prepared or interrupted run with:

content-workflow-cli scene resume --run-dir agentic/runs/RUN_ID

content-workflow-large-scene is an internal transition utility used by the umbrella skill, tests, and recovery. Do not expose it as the user launch command.

Wrapper Responsibilities

• parse workflow inputs;
• create a run directory;
• write request.json;
• start or connect to Workbench;
• launch Codex or Claude Code;
• pass a compact structured task request;
• validate required workflow artifacts;
• require terminal phase validation for a large-scene run;
• preserve logs, traces, and partial outputs.

Agent Responsibilities

The launched agent should use the same skills available in interactive mode, especially:

• content-workbench
• content-workflow-material
• content-workflow-large-scene

Rule

If a task needs custom reasoning, inspection, or recovery, prefer an interactive long-running agent session from agentic/ using the Workbench and workflow skills directly.