Description: <br>
Run tao-daft validate to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. <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 validate NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors before training or deployment. <br>
Deployment Geography for Use: <br>
Global <br>
Requirements / Dependencies: <br>
Requires API Key or External Credential: [No] <br> Credential Type(s): [None] <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>
Skill Output: <br>
Output Type(s): [Shell commands, Analysis] <br> Output Format: [Markdown with inline bash code blocks] <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>
1 evaluation task (1 positive), evaluated with 3 attempts per task per agent 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 selected, decoys were avoided, and the workflow executed. <br>
- Effectiveness: Whether the skill helped complete the user's goal (50% goal completion + 50% expected workflow adherence). <br>
- Efficiency: Whether the skill avoided wasted tool calls and token usage (50% tool-call productivity + 50% token efficiency). <br>
Underlying evaluation signals used in this run: <br>
security: Checks for 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 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. <br>token_efficiency: Actual uncached prompt plus completion token usage. <br>
Evaluation Results: <br>
| Measure | Claude Code (Baseline → Skill Uplift) | Codex (Baseline → Skill Uplift) |
|---|---|---|
| Overall | 94.6% — uplift unavailable | 62.4% — uplift unavailable |
| Security | 100.0% → 100.0% (±0.0 points) | 100.0% → 100.0% (±0.0 points) |
| Correctness | 0.0% → 100.0% (+100.0 points) | 0.0% → 60.0% (+60.0 points) |
| Discoverability | 100.0% — uplift unavailable | 0.0% — uplift unavailable |
| Effectiveness | 5.6% → 100.0% (+94.4 points) | 16.7% → 53.3% (+36.6 points) |
| Efficiency | 72.8% — uplift unavailable | 99.7% → 98.6% (-1.1 points) |
Skill Version(s): <br>
0.1.0 (source: frontmatter) <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>