·
Last changedVersion:
This version passed the hardening gate. The skill content was retained without changes. Classified findings before hardening: 2. Classified findings closed: 0. Classified findings remaining: 2. Unclassified scanner findings remaining: 0. Review findings closed: 0. Review findings remaining: 7.
2
2
Expand | File | Group | Subtype | Severity | Status |
|---|---|---|---|---|---|
references/recipes-knobs-and-constraints.md | Prompt Injection | Direct prompt injection | Medium | Open | |
BENCHMARK.md | Sensitive Data & Secret Exposure | Agent snooping | Medium | Open |
2 findings
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.
input_required, ask only which one to keep, and stop; do not reinterpret a
bitrate as a cap or emit a recipe.input_required,
and stop without emitting a recipe.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.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.failed with the exact reason and do not claim a recipe.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.
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.
low_latency, GOP 60, one B-frame, zero lookahead, full-resolution
multipass, max bitrate 6,000,000, and VBV 3,000,000.unrepresentable in the public PyNvVideoCodec 2.1 sample projection.This skill produces elementary encoder configuration only. Content selection, container/transcode work, independent decode, benchmarking, and evidence capture belong to their owning skills.
Get started with chainctlchainctl skill install public/nvidia/jetson-video-recipe:latest
Bring Chainguard's hardening pipeline to your first-party skills — custom rulesets, automated remediation, full audit trail.
skills.chainreg.biz/public/github.com/nvidia/skills/jetson-video-recipe:latest
Apache-2.0
BENCHMARK.md
HARDENING.md
SKILL.md
evals/evals.json
references/recipes-knobs-and-constraints.md
references/recipes-workflow.md
skill-card.md
skill.oms.sig