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/hsb-setup

@bb0436f
by NVIDIA Corporationnvidia/skills3.5k stars
424

Clone the latest NVIDIA Holoscan Sensor Bridge repo, ask which supported devkit is being used, configure the host per platform, build the correct demo container, run it, and verify HSB connectivity by pinging 192.168.0.2. Use for Holoscan Sensor Bridge setup, build, container launch, and first-connectivity bring-up.

Use this Skill: https://skilld.dev/gh/nvidia/skills/hsb-setup

This session only. Nothing lands on disk.

BENCHMARK.md

≈992 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Evaluation Report

Evaluation of the hsb-setup skill before publication through NVSkills-Eval.

This benchmark summarizes 3-Tier Evaluation from NVSkills-Eval results for the skill. The goal is to document whether the skill is safe, discoverable, effective, and useful for agents before it is published for broader workflow use.

Evaluation Summary

  • Skill: hsb-setup
  • Evaluation date: 2026-06-30
  • NVSkills-Eval profile: external
  • Environment: astra-sandbox
  • Dataset: 1 evaluation tasks
  • Attempts per task: 1
  • Pass threshold: 50%
  • Overall verdict: PASS

Agents Used

  • claude-code
  • codex

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 (Security): checks for unsafe operations, secret leakage, and unauthorized access.
  • skill_execution (Skill Execution): verifies that the agent loaded the expected skill and workflow.
  • skill_efficiency (Efficiency): checks routing quality, decoy avoidance, and redundant tool usage.
  • accuracy (Accuracy): grades final-answer correctness against the reference answer.
  • goal_accuracy (Goal Accuracy): checks whether the overall user task completed successfully.
  • behavior_check (Behavior Check): verifies expected behavior steps, including safety expectations.
  • token_efficiency (Token Efficiency): compares token usage with and without the skill.

Test Tasks

The benchmark dataset contained 1 evaluation tasks:

  • Positive tasks: 1 tasks where the skill was expected to activate.
  • Negative tasks: 0 tasks where no skill was expected.
  • Unlabeled tasks: 0 tasks where positive/negative intent could not be inferred.

Task composition is derived from the evaluation dataset when possible. Entries with expected_skill set are treated as positive skill-activation cases, while entries with expected_skill: null are treated as negative activation cases.

Results

Dimension Num claude-code codex
Security 1 100% (+0%) 100% (+0%)
Correctness 1 0% (-50%) 97% (+81%)
Discoverability 1 0% (-100%) 89% (+48%)
Effectiveness 1 0% (+0%) 78% (+78%)
Efficiency 1 27% (-68%) 81% (+26%)

Score values show skill-assisted performance. Values in parentheses show uplift versus the no-skill baseline when baseline data is available.

Tier 1: Static Validation Summary

Tier 1 validation passed with observations. NVSkills-Eval ran 1 checks and found 4 total findings.

Top findings:

  • MEDIUM SCHEMA/body_recommended_section: Missing recommended section: '## Examples' (team-skills/holoscan/holoscan-sensor-bridge/hsb-setup/SKILL.md)
  • LOW SCHEMA/unexpected_file: Unexpected 'linux' in skill root (team-skills/holoscan/holoscan-sensor-bridge/hsb-setup/linux)
  • LOW SCHEMA/unexpected_file: Unexpected 'windows' in skill root (team-skills/holoscan/holoscan-sensor-bridge/hsb-setup/windows)
  • LOW SCHEMA/unexpected_file: Unexpected 'docs' in skill root (team-skills/holoscan/holoscan-sensor-bridge/hsb-setup/docs)

Tier 2: Deduplication Summary

This tier was not run or did not produce findings in this report.

Publication Recommendation

The skill is suitable to proceed toward NVSkills-Eval publication based on this benchmark. Skill owners should keep this file with the skill and refresh it when the evaluation dataset, skill behavior, or target agents materially change.

Source: SKILL.md on GitHub

2 warnings3mo3 checks · Risk SAFE
  • Gen Agent Trust Hub3mo

    This skill automates the end-to-end setup and validation of the NVIDIA Holoscan Sensor Bridge (HSB) environment on supported devkits. It handles repository cloning, host network configuration, Docker container builds, and connectivity verification through a structured multi-phase workflow.

  • Socket3mo

    4 alerts: gptAnomaly

  • Snyk3mo

    Risk: MEDIUM · 2 issues

Signed by skilld at bb0436f. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 4 months ago
What it can do
Reads files Edits files Runs commands
author
Holoscan Team <holoscan-team@nvidia.com>
version
1.0.0
tags
[
  "holoscan-sensor-bridge",
  "hsb",
  "setup"
]
All 7 allowed tools
ReadWriteEditMultiEditGrepGlobBash
Other metadata
tools
[
  "Read",
  "Write",
  "Edit",
  "Grep",
  "Glob",
  "Bash"
]
disable-model-invocation
true
metadata
{
  "author": "Holoscan Team <holoscan-team@nvidia.com>",
  "team": "holoscan",
  "tags": [
    "holoscan-sensor-bridge",
    "hsb",
    "setup"
  ],
  "agents": [
    "claude-code",
    "codex"
  ]
}

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