Srednoff 3D Web Production Gate

3D Web Production Gate

Plan 3D web release acceptance for real rendering, interaction, device budgets and usable fallbacks.

A desktop screenshot conceals blank canvases, unsupported renderers, mobile thermal slowdown, lost contexts, leaked GPU resources, and a fallback that leaves users unable to complete the task.

Who This Is For

Frontend release leads responsible for an interactive Three.js, R3F, WebGL, or WebGPU experience on the actual devices their customers use.

What You Get

• A standalone, domain-specific agent workflow with decision rules and stop conditions.
• Evidence requirements, structured report guidance and missing-data handling.
• Synthetic worked examples and supporting reference material.
• Optional offline evidence-precheck source where the licensed delivery allows execution; not an automatic artifact scanner.

Expected Deliverables

• candidate_manifest: code/assets, renderer/backend versions, target matrix, permissions, and tested/emulated/unavailable environments
• budget_contract: requirement, device/workload, units, limits, measurement method, owner, and unresolved budgets
• render_interaction_evidence: actual canvas capture, nonblank signal, reviewed subject/framing, input/state assertions, and artifacts
• performance_lifecycle: raw profile references, budget comparisons, resize/mount/dispose/context scenarios, and limitations
• fallback_accessibility_matrix: injected failure, equivalent task, keyboard/touch/reduced-motion behavior, recovery, and evidence
• gate_report: severity, confidence, impact, PASS/FAIL/NOT_TESTED, blockers, recommendation, validation, owner, and rollback proposal

How The Workflow Proceeds

1. Freeze the candidate/asset revisions and target matrix; reconcile renderer capabilities and note whether each target is tested, emulated, or unavailable.
2. Agree scene-specific budgets before interpreting measurements, covering delivery bytes, startup, frame behavior, memory, and concurrency where relevant; retain missing budgets as unresolved decisions.
3. Load the actual candidate and verify model/texture requests, shader initialization, canvas dimensions, and subject visibility; capture nonblank canvas-pixel evidence plus human-reviewed screenshots.
4. Exercise meaningful input and scene state changes, recording before/after canvas evidence and state assertions; static posters or a nonblank background do not establish working 3D.

The remaining workflow covers validation, failure recovery and an evidence-linked handoff.

Bring These Inputs

• Runnable candidate, immutable revision, asset manifest, renderer/framework versions, and permitted local test scope.
• Primary user task, required interactions, supported renderer/browser/device matrix, and physical-device access constraints.
• Owner-agreed performance and delivery budgets with units, device profiles, network conditions, workload, measurement method, and decision authority.
• Expected no-3D fallback, reduced-motion behavior, accessibility requirements, and allowed fault-injection techniques.

Scope And Compatibility

This is a workflow toolkit used by your connected AI agent, not a hosted service, installed API client, autonomous executor or security/compliance certification. You supply the model, authorized tools and project evidence. It does not provide access to advertising, analytics, billing or production accounts. No business outcome or token saving is guaranteed.

Agensi delivery is agent-only. Do not save or export the proprietary source. If local helper execution is unavailable, the agent follows the review workflow and marks the helper NOT_EXECUTED; no local-script execution is promised for this channel.

Validation Transparency

Packaged offline supplied-evidence checks: PASS. Retained synthetic text-response cases: 8/8; scope PASS_SCOPED. These tests are not real-client task trials or marketplace-runtime certification.

Commercial Use And Support

Use project-specific outputs in personal, business and client work under the included Commercial License 1.0. Historical MIT and third-party rights remain unchanged; mandatory marketplace terms prevail. No proprietary source redistribution is included. Publisher: Ivan Srednoff / Srednoff.Agency.

FAQ

Will it make changes automatically? No. Analysis does not authorize spending, publication, deployment or account mutations.

Are examples client results? No. Examples are explicitly synthetic DEMO DATA.

Does it require Srednoff OS? No. The workflow is standalone; external tools and subscriptions are not included.

Is the launch price a proven optimum? No. It is a scoped introductory price informed by comparable offers, not sales forecasts or fake discounts.