oe-llm-package-detection

oe-llm-package-detection is a skill for Claude Code, Codex from HorizonRobotics/OE-Skills. It costs 101 tokens per session (3,272 once invoked), scanned A, original, Apache-2.0.

A setup checker for the OE-LLM package environment used by tools for large language model compression, compilation, quantization, and device inference.

In plain words
What is it for?
It checks existing configuration, locates the OE-LLM package, verifies compatibility, determines whether GPU Docker is needed, and records the results in a project environment file.
Why use it?
It prevents later model-toolchain tasks from starting without the package path, version, and execution mode they need.

Skill for Claude CodeCodex

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

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is cd $OE_LLM_DIR/llm_compression && bash scripts/calib.sh ....

Good fit It checks existing configuration, locates the OE-LLM package, verifies compatibility, determines whether GPU Docker is needed, and records the results in a project environment file.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/HorizonRobotics/OE-Skills
agentmods
npx agentmods add skills/horizonrobotics/oe-skills/oe-llm-package-detection

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 oe-llm-package-detection

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/horizonrobotics/oe-skills/oe-llm-package-detection"><img src="https://agentmods.dev/badge/skills/horizonrobotics/oe-skills/oe-llm-package-detection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 101 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,272 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 $0.00101 $0.03272
Opus 5 $0.00051 $0.01636
Sonnet 5 $0.00020 $0.00654
Haiku 4.5 $0.00010 $0.00327

Measured 11d ago against content hash a0ce72ea2725, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

oe-llm-package-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 11d 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/oe-llm-package-detection/SKILL.md · 224 lines

How it starts

The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OE-LLM 包环境检测

执行方式

本 Skill 应通过 subagent 执行。 主 agent 在前置检查中发现 .env.oe-llm-package 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(OE-LLM 路径、版本、执行模式),主 agent 读取 .env.oe-llm-package 继续后续流程。

目标

检测 OE-LLM 包路径、版本及本地环境匹配情况,写入 .horizon/.env.oe-llm-package,供后续所有 LLM 工具链任务直接使用。

触发条件

任何涉及 LLM 量化、LLM 压缩、LLM 编译、板端 LLM 推理、LLM 精度评估的任务进入 horizon-router 前,如果 .horizon/.env.oe-llm-package 不存在,顶层 Skill 会中断任务并提示用户

未检测到 OE-LLM 包环境配置(.horizon/.env.oe-llm-package)。请提供 OE-LLM 包路径,或回复"跳过"暂不配置。

  • 用户提供路径 → 进入本检测流程
  • 用户回复"跳过" → 记录跳过(仅当次对话有效,下次仍会提示),继续后续任务

LLM 任务的识别关键词:LLM、大语言模型、VLM、视觉语言模型、llm_compression、AWQ、GPTQ、RTN、SmoothQuant、LLM 量化、LLM 编译、LLM 推理、oellm、InternVL、Qwen-VL、LLaMA 等。

检测流程

1. 检查 .horizon/.env.oe-llm-package 是否存在

  • 文件存在且内容完整(包含 OE_LLM_DIROE_LLM_VERSIONEXECUTION_MODE 等字段)→ 直接读取,跳过后续步骤
  • 文件不存在或不完整 → 进入步骤 2

2. 定位 OE-LLM 包路径

按优先级查找:

  1. 环境变量OE_LLM_DIROPEN_EXPLORER_LLM_DIRHORIZON_OE_LLM_DIR
  2. 项目配置文件.env.horizon/oe-llm.envCLAUDE.md 中声明的路径
  3. 常见路径探测/open_explorer_llm~/open_explorer_llm/opt/openexplorer_llm,以及 /mnt/oe-cli-test/ 下以 horizon_j6_open_explorer_llm 开头的目录
  4. 以上都没有 → 询问用户 OE-LLM 包路径

找到路径后,验证目录中存在 OE-LLM 包的标志性文件(以下至少两个):

  • run_docker.sh
  • llm_compression/ 目录
  • runtime/ 目录

注意:OE-LLM 包没有标准 OE 包的 samples/docs/toolchain/ 目录,也没有 package/host/ai_toolchain/ 子目录。

3. 采集 OE-LLM 版本信息

从 OE-LLM 包目录中提取以下信息:

OE-LLM 包整体版本

  • 从目录名提取(如 horizon_j6_open_explorer_llm_v2.0.0_rc3-py310_20260615v2.0.0_rc3
  • 检查 README-CNREADME-EN 中的版本信息
  • 以上都无法确定时询问用户

组件版本(从 llm_compression/deps_version.conf 解析):

字段 含义 示例值
HBDK_VERSION HBDK4 编译器版本 4.11.2
HORIZON_PLUGIN_PYTORCH_VERSION PyTorch 量化插件版本 3.3.4
HBM_INFER_VERSION HBM 推理引擎版本 3.15.3
LLM_COMPRESSION_VERSION LLM 压缩工具版本 2.0.2
TORCH_VERSION 配套 PyTorch 版本(含 CUDA) 2.8.0+cu128
PYTHON_VERSION 配套 Python 版本 py310

Read the full file on GitHub · 224 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. 11d ago First seen · 224 lines · 101 tokens per session scan A a0ce72ea2725

Subscribe to this mod's changes

oe-llm-package-detection is a skill published in the GitHub repository HorizonRobotics/OE-Skills (19 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 101 tokens to every session and 3,272 once invoked, about $0.0005 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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