القائمة
Design and run controlled Sume quality experiments with one-variable variants, reusable manifests, side-by-side artifact comparison, and rubric-based sanitized reports.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | sume-quality-experiment |
| description | Design and run controlled Sume quality experiments with one-variable variants, reusable manifests, side-by-side artifact comparison, and rubric-based sanitized reports. |
Use this skill for controlled Avatar or Avatar Video comparisons.
sume tools schema avatar-videos.create --json
sume avatar-videos batch plan ./experiment.videos.json --output-file ./experiment.plan.json --json
sume avatar-videos batch create ./experiment.videos.json --state-file ./experiment.state.json --confirm-paid --json
sume avatar-videos batch watch ./experiment.videos.json --state-file ./experiment.state.json --json
sume avatar-videos batch result ./experiment.videos.json --state-file ./experiment.state.json --json
Use sume-media-qa after results exist if the user needs local files, still
sheets, codec checks, or side-by-side comparison.
Score or summarize:
Do not use this skill for unrestricted exploration, raw provider endpoint
tests, or one-off fastest iteration. Use sume-min-latency for speed and
sume-spend-capped-dogfood for paid QA with a strict budget.
Create, batch-plan, watch, inspect, and select current Sume Avatar 1.0 resources by avatar_handle with safe paid gates and agent-redacted readback.
Create, batch-plan, watch, and inspect Sume Avatar Video 1.0 jobs from selected avatar handles, including productless/product-image flows, metadata readback, and paid gates.
Run the fastest safe Sume Avatar/Avatar Video iteration loop using async submits, batch state files, parallel polling, deferred downloads, and explicit quality/cost tradeoffs.
Router for current Sume.com public API workflows. Use for auth, schema discovery, Avatar 1.0, Avatar Video 1.0, jobs, spend-capped dogfooding, minimum-latency generation loops, media QA, and selecting focused Sume skills.
Run paid Sume dogfood QA under an explicit USD cap using idempotency, max_spend_usd where available, cost readback, and no duplicate paid submissions.
Use advanced compatibility Sume asset upload/download helpers only when explicitly requested; launch Avatar and Avatar Video inputs should use stable public HTTPS URLs directly.