board-detection

board-detection is a skill for Claude Code, Codex from HorizonRobotics/OE-Skills. It costs 72 tokens per session (2,166 once invoked), scanned A, original, Apache-2.0.

A setup skill that detects the hardware board used for board-side software work and records its connection and platform details in the project.

In plain words
What is it for?
It is for preparing board-based builds, inference, remote HBM work, performance tests, and BPU measurements, or falling back to offline x86 checks when no board is available.
Why use it?
It avoids repeating hardware checks and warns when a task needs a board that is unavailable or not configured.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md; mentions subagents; mentions AGENTS.md.

Good fit It is for preparing board-based builds, inference, remote HBM work, performance tests, and BPU measurements, or falling back to offline x86 checks when no board is available.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/horizonrobotics/oe-skills/board-detection
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add HorizonRobotics/OE-Skills --skill board-detection
Clone the repo
git clone --depth 1 https://github.com/HorizonRobotics/OE-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for board-detection

README.md
[![agentmods](https://agentmods.dev/badge/skills/horizonrobotics/oe-skills/board-detection/github.svg)](https://agentmods.dev/skills/horizonrobotics/oe-skills/board-detection)
Your own site
<a href="https://agentmods.dev/skills/horizonrobotics/oe-skills/board-detection"><img src="https://agentmods.dev/badge/skills/horizonrobotics/oe-skills/board-detection/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for board-detection

Your own site · 80×15
<a href="https://agentmods.dev/skills/horizonrobotics/oe-skills/board-detection"><img src="https://agentmods.dev/badge/skills/horizonrobotics/oe-skills/board-detection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,166 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.02166
Opus 5 $0.00036 $0.01083
Sonnet 5 $0.00014 $0.00433
Haiku 4.5 $0.00007 $0.00217

Measured 12d ago against content hash 85336343ae65, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

board-detection scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

horizon/skills/horizon-router/board-detection/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

板卡硬件平台检测

执行方式

本 Skill 应通过 subagent 执行。 主 agent 在前置检查中发现 .env.board 缺失或不完整时,应将本文件的完整内容作为 subagent prompt 派发执行。subagent 完成后汇报写入结果和需要用户确认的事项(如有),主 agent 读取 .env.board 继续后续流程。

目标

检测用户的板卡硬件平台信息,写入 .horizon/.env.board,供后续所有板端任务直接使用。

板卡检查规则

  • 板卡类型按三类处理:nash-e/m(Linux)、nash-p(Linux)与 nash-b(QNX)
  • 优先从环境变量中查找板卡信息,例如 HORIZON_BOARD_TYPEOE_BOARD_TYPEBOARD_TYPEBOARDNASH_BOARD
  • 如果环境变量没有提供,再检查项目内相关配置文件,例如 .env.env.local.horizon/board.env.horizon/board.jsonAGENTS.mdCLAUDE.md
  • 如果任务涉及板端运行、板端推理、远端 HBM、性能压测或 BPU 实测,但没有找到板卡信息,必须先向用户确认是否有可用板卡
  • 如果用户明确没有可用板卡,涉及板端的任务应回退到 X86 评测、仿真、静态检查或可离线执行的分析工具,并说明该结果不能替代真实板端验证
  • nash-b 板卡为可选项:用户可以跳过 nash-b 配置,但系统必须给出明确提示:"已跳过 nash-b 板卡配置。后续涉及 nash-b 板端的任务将不可用,仅可在 X86 环境进行编译和离线分析。如需启用,请删除 .horizon/.env.board 重新执行板卡检测。"
  • 板卡工作目录(BOARD_WORKDIR)也是 .env.board 完整性的必要字段。如果文件中缺少该字段,需要重新执行工作目录检测(步骤 3.5)

检测流程

  1. 检查 .horizon/.env.board 是否存在

    • 文件存在且内容完整(包含 BOARD_TYPEBOARD_IPBPU_ARCHBOARD_WORKDIR 等字段)→ 直接读取,跳过后续步骤
    • 文件不存在或不完整(含缺少 BOARD_WORKDIR)→ 进入步骤 2
  2. 获取板卡 IP

    • 先读取项目根目录 .env 文件,查找 BOARD_IPBOARD_IP_NASH_PBOARD_IP_NASH_B 等字段
    • 如果 .env 中有板卡 IP → 进入步骤 3
    • 如果 .env 中没有 → 询问用户是否有可用板卡 IP
      • 用户提供了 IP → 进入步骤 3
      • 用户明确表示没有可用板卡 → 跳过本阶段,说明"当前任务将回退到 X86 评测或仿真模式,结果不能替代真实板端验证"
  3. 自动检测板卡架构

    • 使用 SSH 连接板卡(默认用户名 root),执行:
      uname -a
      hrut_somstatus
      
    • 从输出中自动解析架构、内核版本、镜像日期、BPU 状态等信息
    • 根据 .env 中 IP 与变量的对应关系自动判断板卡类型:
      • BOARD_IP / 无后缀 → nash-e/m(Linux 平台)
      • BOARD_IP_NASH_P / _NASH_P 后缀 → nash-p(Linux 平台)
      • BOARD_IP_NASH_B / _NASH_B 后缀 → nash-b(QNX 平台,uname -a 输出含 QNX
    • nash-b (QNX) 特殊说明:nash-b 运行 QNX 实时操作系统,SSH 连接后 uname -a 的输出格式与 Linux 不同(系统名为 QNX,无发行版信息)。hrut_somstatus 命令仍可用。如果 SSH 连接或命令执行失败,可能是 QNX 板卡的 SSH 服务配置不同,需要向用户确认
    • 全程不需要用户手动确认架构信息,全部自动推断
    • 跳过选项:对于每种板卡类型,用户都可以选择跳过。跳过时给出明确提示:

      ⚠️ 已跳过 [板卡类型] 的配置。后续涉及该板卡的板端任务将不可用。如需启用,请删除 .horizon/.env.board 重新执行板卡检测。

Read the full file on GitHub · 117 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 117 lines · 72 tokens per session scan A 85336343ae65

Subscribe to this mod's changes

board-detection is a skill published in the GitHub repository HorizonRobotics/OE-Skills (19 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 72 tokens to every session and 2,166 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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