Description: <br>
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. <br>
This skill is ready for commercial/non-commercial use. <br>
Owner
NVIDIA <br>
License/Terms of Use: <br>
Apache-2.0 <br>
Use Case: <br>
Developers and engineers use this skill to query, classify, and reconcile Jetson hardware video codec capabilities from live APIs, authenticated NVIDIA samples, and official NVIDIA documentation. <br>
Deployment Geography for Use: <br>
Global <br>
Requirements / Dependencies: <br>
Requires API Key or External Credential: [Not Specified] <br> Credential Type(s): [None identified] <br>
Do not include secrets in prompts/logs/output; use least-privilege credentials; rotate keys as appropriate. <br>
Known Risks and Mitigations: <br>
Risk: Review before execution as proposals could introduce incorrect or misleading guidance into skills. <br> Mitigation: Review and scan skill before deployment. <br>
Reference(s): <br>
- Capability query guidance <br>
- Surface selection contract <br>
- NVIDIA Video Encode and Decode Support Matrix <br>
- NVENC Application Note (SDK 13.0) <br>
- NVDEC Application Note (SDK 13.0) <br>
Skill Output: <br>
Output Type(s): [Analysis] <br> Output Format: [Markdown] <br> Output Parameters: [1D] <br> Other Properties Related to Output: [None] <br>
Evaluation Agents Used: <br>
- Claude Code (
aws/anthropic/bedrock-claude-opus-4-8) <br> - Codex (
openai/openai/gpt-5.5) <br>
Evaluation Tasks: <br>
5 evaluation tasks (5 positive) with 3 attempts per task in isolated k8s-sandbox pods. <br>
Evaluation Metrics Used: <br>
Reported benchmark dimensions: <br>
- Security: Whether the skill is safe to use: checks for unsafe operations, secret leakage, and unauthorized access. <br>
- Correctness: Whether the answer is correct against the reference answer. <br>
- Discoverability: Whether the right skill was loaded when needed: skill selection, decoy avoidance, and workflow execution. <br>
- Effectiveness: Whether the skill helped complete the task: goal completion (50%) and expected workflow adherence (50%). <br>
- Efficiency: Whether wasted tool calls and token usage were avoided: tool-call productivity (50%) and token efficiency (50%). <br>
Underlying evaluation signals used in this run: <br>
security: Unsafe operations, secret leakage, and unauthorized access. <br>accuracy: Final-answer correctness against the reference answer. <br>skill_execution: Whether the expected skill was selected, decoys were avoided, and the workflow executed. <br>goal_accuracy: Whether the user's goal was achieved. <br>behavior_check: Whether the expected workflow behavior was followed. <br>skill_efficiency: Tool-call productivity (legacy wire id; routing scored under Discoverability). <br>token_efficiency: Actual uncached prompt plus completion usage. <br>
Evaluation Results: <br>
| Measure | Claude Code (Baseline → Skill Uplift) | Codex (Baseline → Skill Uplift) |
|---|---|---|
| Overall | 90.0% | 88.6% |
| Security | 100.0% → 100.0% (±0.0 points) | 100.0% → 100.0% (±0.0 points) |
| Correctness | 90.0% → 96.0% (+6.0 points) | 86.7% → 96.0% (+9.3 points) |
| Discoverability | 96.0% | 93.0% |
| Effectiveness | 55.3% → 63.0% (+7.7 points) | 69.4% → 75.3% (+5.9 points) |
| Efficiency | 95.0% | 78.8% |
Skill Version(s): <br>
74bce4d (source: git SHA, committed 2026-09-16) <br>
Ethical Considerations: <br>
NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal team to ensure this skill meets requirements for the relevant industry and use case and addresses unforeseen product misuse. <br>
(For Release on NVIDIA Platforms Only) <br> Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here. <br>