Agent Skills / FPGA flashing

HSB · Agent Skill

FPGA flashing

Flash the FPGA on an HSB board connected to an NVIDIA devkit. Supports HSB Lattice boards (FPGA versions 2407, 2412, 2507, 2510) and Leopard Imaging VB1940 "all-in-one" cameras (FPGA versions 2507, 2510). Uses release-specific YAML manifests and board-type-specific program commands. Lattice and VB1940 commands must never be mixed.

Install

npx skills add nvidia/skills --skill hsb-flash

Add --agent cursor, --agent claude-code, --agent codex, or --agent kiro-cli to target a specific agent.

At a glance

Skill	hsb-flash
Product	Holoscan Sensor Bridge
Version	1.0.0
License	Apache-2.0
Tags	holoscan-sensor-bridge, hsb, fpga-flashing
Source	NVIDIA/skills ↗

This skill is ready for commercial/non-commercial use.

Owner

NVIDIA

Use Case

Developers and engineers who need to flash (upgrade or downgrade) FPGA firmware on Holoscan Sensor Bridge boards connected to NVIDIA devkits.

Deployment Geography for Use

Global

Known Risks and Mitigations

Risk: Review before execution as proposals could introduce incorrect or misleading guidance into skills.
Mitigation: Review and scan skill before deployment.

Reference(s)

• Flashing Infrastructure
• Help Text
• Phase Details
• Holoscan Sensor Bridge Release Notes

Skill Output

Output Type(s): [Shell commands, Configuration instructions]
Output Format: [Markdown with inline bash code blocks]
Output Parameters: [1D]
Other Properties Related to Output: [None]

Evaluation Agents Used

• claude-code
• codex

Evaluation Tasks

Evaluated against 3 internal evaluation tasks (positive skill-activation cases, 2 attempts per task, 50% pass threshold).

Evaluation Metrics Used

Reported benchmark dimensions:

• Security: Checks whether skill-assisted execution avoids unsafe behavior such as secret leakage, destructive commands, or unauthorized access.
• Correctness: Checks whether the agent follows the expected workflow and produces the correct final output.
• Discoverability: Checks whether the agent loads the skill when relevant and avoids using it when irrelevant.
• Effectiveness: Checks whether the agent performs measurably better with the skill than without it.
• Efficiency: Checks whether the agent uses fewer tokens and avoids redundant work.

Underlying evaluation signals used in this run:

• security: Checks for unsafe operations, secret leakage, and unauthorized access.
• skill_execution: Verifies that the agent loaded the expected skill and workflow.
• skill_efficiency: Checks routing quality, decoy avoidance, and redundant tool usage.
• accuracy: Grades final-answer correctness against the reference answer.
• goal_accuracy: Checks whether the overall user task completed successfully.
• behavior_check: Verifies expected behavior steps, including safety expectations.
• token_efficiency: Compares token usage with and without the skill.

Evaluation Results

Dimension	Num	claude-code	codex
Security	6	100% (+0%)	100% (+0%)
Correctness	6	100% (+0%)	94% (+49%)
Discoverability	6	98% (+3%)	78% (+27%)
Effectiveness	6	97% (-0%)	88% (+69%)
Efficiency	6	85% (+6%)	68% (+28%)

Ethical Considerations

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.

(For Release on NVIDIA Platforms Only)
Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

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