name: jetson-video-recipe license: "Apache-2.0" description: >- Use when turning a Jetson encoder use case into one surface-neutral recipe with native Video Codec SDK and PyNvVideoCodec projections. metadata: author: "Vinit Bansal vinitkumarb@nvidia.com" tags: [jetson, video-codec-sdk, pynvvideocodec, nvenc, recipe] languages: [markdown] data-classification: public

Jetson Video Recipe

Create one deterministic nvcodec-recipe schema 2.0 document. Recipe work is off-target and media-free: it does not probe, install, encode, decode, or claim support, quality, or performance.

Boundaries

• For a request solely about PSNR, SSIM, or another objective quality metric, say that a separately authorized quality workflow is required and stop.
• Resolve a supplied CQ plus average or maximum bitrate conflict first. Return input_required, ask only which one to keep, and stop; do not reinterpret a bitrate as a cap or emit a recipe.
• An unqualified “low latency” does not select a use case. Ask whether it means conferencing, live streaming, or another contract, return input_required, and stop without emitting a recipe.
• Preserve every explicit control. If one surface cannot express it, publish a projection loss; never silently discard or weaken it.

Workflow

1. Collect use case, codec, positive integer width/height/fps, input format, GPU, and any explicit profile, preset, tuning, rate-control, bitrate, GOP, B-frame, lookahead, AQ, multipass, or buffering controls. frame_count is required before raw encode or measurement, but may remain unknown until an authenticated decoder/transcoder reports it for compressed input. If use_case, width, or height is missing, return input_required naming exactly the missing items and stop; apply the documented defaults for every other omitted item. Leave omitted profile SDK-selected.
2. Apply the fixed defaults and constraints in recipes-knobs-and-constraints.md, then build the schema-2 document exactly as described in recipes-workflow.md. Keep caller values and defaults separately attributable.
3. Validate the document structurally: exact schema/kind; finite JSON; positive bounded integers; legal enum strings; mutually exclusive rate-control fields; format/profile constraints; projections derived from the same encoder_intent; and every explicit caller control represented in each projection or named in that projection's losses. Regenerate rather than editing an accepted recipe. If the regenerated document still fails structural validation, return failed with the exact defect and do not emit a recipe.
4. Write canonical, sorted JSON to a fresh path without overwriting anything. Record its canonical absolute path, byte count, and SHA-256; every consumer rehashes that exact file. If no safe fresh path exists or writing/rehashing fails, return failed with the exact reason and do not claim a recipe.
5. Return the intent, assumptions/defaults, both projections, all losses, and the recipe file's canonical absolute path, byte count, and SHA-256. For both, retain both outcomes. auto means retain both projections without selecting either; the pipeline or benchmark selects from fresh live eligibility evidence.

For a plan-only recipe, these Markdown rules are the complete authority. Do not probe the target, inspect installed SDK/sample source, scan the filesystem for example JSON, or invoke another skill merely to confirm the projection. Plan-only still requires steps 2-5, including writing and rehashing the fresh canonical recipe JSON and reporting its absolute path, byte count, and SHA-256; it forbids target and media operations, not local recipe-artifact creation.

Live and downstream work

For a requested live classification, obtain a fresh read-only readiness result from jetson-video-setup for the selected product and GPU, plus the applicable raw/documentation result from jetson-video-capability. Missing facts remain unknown; explicit negatives or an unrepresentable projection are unsupported. API-reported capability is not operation proof.

Pass the original recipe identity as data to jetson-video-pipeline for execution or jetson-video-benchmark for measurement. Those skills must rehash it and hold non-compared controls constant. Do not import or recreate a sibling skill's implementation.

Required outcomes

• H.264 1920x1080@60, 6 Mbps CBR live streaming defaults to P4, low_latency, GOP 60, one B-frame, zero lookahead, full-resolution multipass, max bitrate 6,000,000, and VBV 3,000,000.
• An explicit H.264 High profile is exact in the native projection and unrepresentable in the public PyNvVideoCodec 2.1 sample projection.
• A CQ plus average bitrate request produces no recipe until resolved.

Limitations

This skill produces elementary encoder configuration only. Content selection, container/transcode work, independent decode, benchmarking, and evidence capture belong to their owning skills.