jetson-video-capability
Use when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled from live APIs, authenticated NVIDIA samples, and NVIDIA documentation; also applies the content-DRM scope.
Install / Use
npx skills add NVIDIA/skills --skill jetson-video-capabilityInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Content & MediaSupported Platforms
Our assessment of jetson-video-capability
jetson-video-capability scores 85/100 on our quality scale, 457th of 770 Content & Media skills we index.
Its SKILL.md is 7.6 KB long, split into 5 sections and no code examples: a thorough specification that gives an agent plenty to work with.
With 3,421 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 5 days ago, so jetson-video-capability is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
jetson-video-capability compared with similar skills
All 4 of these similar skills score higher than jetson-video-capability; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| jetson-video-capability (this skill)by NVIDIA | 85 | 3.4k | 5d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 86.0k | 13d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.0k | today | CLAUDE.md |
| crawl4aiby unclecode | 100 | 84.4k | 3d ago | MCP Server |
| Scraplingby D4Vinci | 100 | 84.4k | today | MCP Server |
Frequently asked questions
- How do I install jetson-video-capability?
- Run
npx skills add NVIDIA/skills --skill jetson-video-capability. The install tabs above show the steps for each supported agent. - Which AI agents does jetson-video-capability work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is jetson-video-capability safe to use?
- It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is jetson-video-capability still maintained?
- The repository was last updated 5 days ago, so jetson-video-capability is actively maintained.
Skill content
View source on GitHubname: jetson-video-capability license: "Apache-2.0" description: >- Use when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled from live APIs, authenticated NVIDIA samples, and NVIDIA documentation; also applies the content-DRM scope. metadata: author: "Vinit Bansal vinitkumarb@nvidia.com" tags: [jetson, video-codec-sdk, pynvvideocodec, nvenc, nvdec, capability] languages: [markdown] data-classification: public
Jetson Video Capability
Keep three authorities separate:
- API query: raw fields, never operation or product-support proof.
- Authenticated NVIDIA sample: report or exact operation evidence.
- Applicable NVIDIA documentation: product-support verdict.
Scope gates
- For a request solely for PSNR, SSIM, or other objective quality metrics, say this skill does not provide them and a separately authorized quality workflow is required; do nothing else.
- For Netflix, Widevine, PlayReady, or clearly content-protected streaming, state only that this skill covers hardware encode/decode of user-supplied non-DRM bitstreams, not content-DRM playback. Do not claim whether the service works, describe Jetson certification, CDM, or secure-playback requirements, or recommend a browser, DRM module, workaround, or bypass; then stop. An unqualified “DRM” may mean Linux DRM/KMS; ask which meaning if context does not resolve it.
- A bare “video SDK” is ambiguous: ask native Video Codec SDK, PyNvVideoCodec, or both before probing. An otherwise unqualified capability request uses the native-preferred fallback in surface-selection-contract.md.
Read-only discovery
Capability work depends on jetson-video-setup for a fresh, read-only
installation check. Invoke that skill through public dispatch and consume its
reported exact native package/Samples root or exact PyNvVideoCodec interpreter,
version, and loaded module path. Do not locate or import setup's files. A
missing or mismatched surface is unknown/not_ready, never codec unsupported;
route repair to setup without mutating anything here.
Engine capability queries belong here, not in setup. For PyNvVideoCodec, use
the exact selected interpreter to call the public GetEncoderCaps and
GetDecoderCaps APIs as described in
capability-queries.md. A broad encoder
catalog covers H.264, HEVC, and AV1; a broad decoder catalog covers all ten
families across four chroma formats and three bit depths (120 exact tuples).
A bounded request queries only named members of the applicable catalog set.
Preserve every scoped record, error, and GPU ordinal. Nonzero-GPU helper results
remain unknown when the public helper selects only GPU 0.
For native reports, reuse authenticated package-owned binaries or build only
the required report target in a fresh user-owned tree, then run
AppEncCuda -ec and/or AppDec -dc using the build, identity, and grammar
rules in the capability reference. A query-only request does not authorize
package installation or an encode/decode operation. If the package, source,
tool, interpreter, or runtime-library identity cannot be established, report
the result unknown and name the missing setup prerequisite.
Decision flow
- Classify scope and selected surface before any probe.
- Query only the selected surface. Preserve raw records, errors, exact GPU, release, interpreter/binary identities, argv, and evidence classification.
- Resolve the most exact live product identity using the device-tree paths and NUL handling in capability-queries.md, then cross-check it against NVIDIA's current Video Encode and Decode Support Matrix and the release-matched SDK 13.0 NVENC or NVDEC application note. Never infer SKU from memory, engine count, capability fields, or operation behavior. Preserve source URL, retrieval date, table title, exact row/column labels, and cell value, using that reference's manual capture record. Generic family identity stays non-exact; use candidate-row consensus only when every authenticated candidate agrees.
- Report documentation
Noas the final unsupported product verdict even if an API or diagnostic operation is positive; this ends the normal availability check. DocumentationYesestablishes documented support; live availability additionally needs the matching authenticated operation. Missing, unretrievable, or conflicting documentation remains unknown. When documentation is unknown, do not present positive capability fields as available options: label each affected codecunknownbeside them and state the retrieval failure with the verdict. - For a PyNvVideoCodec encode-availability operation, request setup's
full-samplesprofile and carry its exact interpreter into the recipe and pipeline stages. Do not select the smaller decode-performance/smoke profile. - Run an exact operation only when the user requests live availability and
documentation is positive or unknown, or explicitly requests a diagnostic
despite a negative verdict. A diagnostic under documentation
Noreports onlyoperation_verifiedoroperation_failedfor that exact tuple and never changes the unsupported product verdict. A tuple is the exact surface, GPU, codec, profile, chroma, bit depth, dimensions, input format, and control set tested. Resolve one recipe withjetson-video-recipe, then usejetson-video-pipelinefor encode followed by independent decode of the exact output identity. A failed tuple never generalizes to the product.
Evidence rules
GetEncoderCapssuccess iscapability_reported,supported=null,operation_status=not_tested.GetDecoderCapsbIsSupported=1/0records raw API true/false and whether returned limits apply; neither value is the documentation verdict.- Missing enums, calls, fields, prerequisites, or nonzero-GPU authority are unknown, not unsupported.
- Native
-ec/-dctext isofficial_sample_report; preserve raw values and never rewrite them as API or product claims. - When reporting Main10 support, note that NVENC can convert verified 8-bit input internally and that P010 is the exact no-input-bit-depth-conversion path; a live claim still requires an authenticated 10-bit operation.
- AV1 output is operation evidence only after the pipeline's package-owned decoder consumes the exact artifact and reports the expected frame count.
- For a VP9 encode question, report only that VP9 remains a decoder family and no released NVENC route exists. Do not add a generic list of other encoders or offer a diagnostic encode operation.
- Presets, tuning, package presence, throughput, and successful concurrent streams do not establish codec support or NVENC/NVDEC engine count.
- Codec/API capability, NVENC/NVDEC availability, and successful bounded operations do not establish DMA-BUF, NvSciBuf, CUDA-memory sharing, zero copy, or cross-stage synchronization compatibility.
For a Python API query, create a short task-local program from this Markdown and the installed public SDK, run it with the exact selected interpreter, and keep its raw output with the result. Installation belongs to setup and operation validation belongs to pipeline. This skill owns engine queries, classification, documentation reconciliation, and the compact direct report above.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
