llmcompression-operations

llmcompression-operations is a skill for Claude Code, Codex from HorizonRobotics/OE-Skills. It costs 145 tokens per session (3,228 once invoked), scanned A, original, Apache-2.0.

Um guia para as operações diárias da ferramenta llm_compression, usada para calibrar, avaliar, compilar e executar modelos de linguagem em placas. Um modelo de linguagem é um sistema de aprendizagem automática que processa e gera texto.

In plain words
What is it for?
Serve para executar os scripts padrão de calibração, avaliação, compilação e inferência no dispositivo, usando os ficheiros de configuração a partir da raiz do pacote.
Why use it?
Evita erros de importação causados por executar os scripts dentro da pasta errada. O guia explica que os comandos devem ser executados a partir da raiz do projeto, porque existe uma pasta local com o mesmo nome de uma biblioteca externa.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is bash llm_compression/scripts/calib.sh --config_path llm_compression/configs/qwen3_vl.yml.

Good fit Serve para executar os scripts padrão de calibração, avaliação, compilação e inferência no dispositivo, usando os ficheiros de configuração a partir da raiz do pacote.

Compare 6 skills from other repositories ↓
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/llmcompression-operations

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.

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README.md
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Your own site
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Per session 145 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,228 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 $0.00145 $0.03228
Opus 5.5 $0.00058 $0.01291
Sonnet 5.5 $0.00029 $0.00646
Haiku 4.5 $0.00015 $0.00323

Measured 2mo ago against content hash 28e495fdd4f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

llmcompression-operations 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 2mo 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/llm/llm_compression/llmcompression-operations/SKILL.md · 221 lines

How it starts

The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LLM Compression 日常操作

llm_compression 是独立于 OE / OE-LLM 的 LLM 工具链包,提供校准、评测、编译、板端推理等标准脚本。

与 llmcompression-add-model 的区分:新增模型架构支持(编写 blocks/、model.py 等)请路由到 llmcompression-add-model;运行校准/评测/编译/板端推理等日常操作使用本 Skill。


⛔ 关键规则

⛔⛔ 执行目录:必须从项目根目录运行(禁止 cd 进 llm_compression/)

这是最常见的致命错误。 cd 进 llm_compression/ 会导致 Python 循环引用,所有脚本在 import 阶段即崩溃。

llm_compression/ 目录下有一个 datasets/ 子包,与第三方库 datasets(HuggingFace)同名。当 CWD 为 llm_compression/ 时,Python 的 sys.path[0]=''(CWD)会优先搜索到本地 datasets/ 子包,遮蔽第三方库,触发:

ImportError: cannot import name 'load_dataset' from partially initialized module 'datasets'
(most likely due to a circular import)

正确做法 — 从 OE LLM 包根目录(llm_compression/ 的父目录)执行脚本:

# ✅ 正确:CWD = 项目根目录
cd ${OE_LLM_DIR}   # 即 /open_explorer_llm
bash llm_compression/scripts/calib.sh --config_path llm_compression/configs/qwen3_vl.yml

# ❌ 错误:CWD = llm_compression/ → circular import
cd ${OE_LLM_DIR}/llm_compression
bash scripts/calib.sh --config_path configs/qwen3_vl.yml

所有标准脚本的路径和配置路径都必须从项目根目录相对书写:

操作 ✅ 正确命令(CWD = 项目根目录)
校准 bash llm_compression/scripts/calib.sh --config_path llm_compression/configs/<model>.yml
GPU 精度评测 bash llm_compression/scripts/torch_eval.sh --config_path llm_compression/configs/<model>.yml
HBM 编译 bash llm_compression/scripts/compile.sh --config_path llm_compression/configs/<model>.yml
板端精度评测 bash llm_compression/scripts/hbm_rpc_eval.sh --config_path llm_compression/configs/<model>.yml
量化误差分析 bash llm_compression/scripts/quant_analysis.sh --config_path llm_compression/configs/<model>.yml

⛔ 必须通过 scripts/.sh 入口执行(禁止直接调用 tools/.py)

即使你已经理解了 shell 脚本的内部实现,也禁止绕过它。 标准脚本会自动处理 PYTHONPATH、环境变量、CWD 和日志,直接调用 Python 可能触发不可预见的问题(如循环引用、路径错误)。

操作 ✅ 正确(通过 shell 入口) ❌ 禁止(直接调 Python)
校准 bash llm_compression/scripts/calib.sh --config_path <yml> python3 llm_compression/tools/calib.py ...
GPU 评测 bash llm_compression/scripts/torch_eval.sh --config_path <yml> python3 llm_compression/tools/torch_eval.py ...
编译 bash llm_compression/scripts/compile.sh --config_path <yml> python3 llm_compression/tools/compile.py ...
板端评测 bash llm_compression/scripts/hbm_rpc_eval.sh --config_path <yml> python3 llm_compression/tools/hbm_rpc_eval.py ...
量化分析 bash llm_compression/scripts/quant_analysis.sh --config_path <yml> python3 llm_compression/tools/quant_analysis.py ...

Read the full file on GitHub · 221 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. 2mo ago First seen · 221 lines · 145 tokens per session scan A 28e495fdd4f0

Subscribe to this mod's changes

llmcompression-operations is a skill published in the GitHub repository HorizonRobotics/OE-Skills (27 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 145 tokens to every session and 3,228 once invoked, about $0.0006 per session on Opus 5.5. 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.

Related

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