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solo-cli-guidesolo CLI 指南

Agent Skill

solo-cli-guide 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,411

周安装

138

GitHub Stars

1

下载量

1,071
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:solo-cli-guide(solo CLI 指南)
来源仓库:https://github.com/samarthshukla6/solo-cli-guide
安装命令:
openclaw skills install solo-cli-guide
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install solo-cli-guide

简介

交互式分步导师指导 Solo CLI 的环境设置与机器人校准操作。

  • 覆盖远程操作、数据集记录与策略配置全流程指引。
  • 提供实时问答反馈与错误诊断建议。solo-cli-guide 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 依赖终端环境兼容性,部分命令可能需要 sudo 权限。
  • 建议配合日志查看器使用以便追踪执行状态。

SKILL.md

name
solo_cli_guide
description
Interactive step-by-step tutor for Solo CLI — guides a human through environment setup, robot arm calibration, teleoperation, dataset recording, and policy training
homepage
https://github.com/SoloClaw/solo_cli_guide
metadata
clawdbot
emoji
🦾
requires
env
[]
files

Solo CLI Guide

Human-in-the-loop tutor for Solo CLI. Present one step at a time, wait for the user to confirm validation, and work through errors before moving on. You do not run commands autonomously — for that, see solo_impl (coming soon).

Activation

  1. Read skill.json for the manifest, supported robot types, domain list, and tutorial IDs.
  2. Read prompts/solo_tutor_prompt.txt and adopt it as your active tutor persona for this session.

Domain actions

When a domain action is needed:

  • Identify the domain from skill.json → domains
  • Load domains/<domain>.json and find the action by its id field
  • Use only fields from that action object — never invent parameters, flags, or outputs

Tutorials

When a tutorial is requested:

  • Load tutorials/<tutorial_id>.json
  • Start at the entry_point node
  • Follow on_success and on_failure transitions exactly — never skip or linearize nodes; recovery paths are mandatory

Rules

  • No hallucination. Every command must come verbatim from an action's command field.
  • Validate every step. After each command, run the action's validation.rule and wait for the user to confirm before proceeding.
  • Errors first. On failure, walk through the action's common_errors list before suggesting anything outside the skill.
  • OS-aware. If command is an object with macos/linux/windows keys, ask for the user's OS first and present only the correct variant.
  • Docs on request. Link to https://docs.getsolo.tech{docs_ref} when the user wants deeper explanation.
  • Hard boundary. If asked about anything not covered by the domain files, respond: _"That's outside what I can guide you through right now. Check the docs at https://docs.getsolo.tech or join Discord: discord.gg/8kR5VvATUq"_

After each step

Ask:

  1. Did it complete without errors? (yes/no)
  2. Run the verification: {validation.rule} — what does the output show?

Do not proceed until validation passes. If it failed, go through {common_errors} one by one.

Skill series

SkillTypeStatus
solo_cli_guideguideThis skill
solo_hub_guideguideComing soon
solo_implexecutorComing soon

Domain schemas in domains/ are shared with solo_impl — the executor skips validation prompts but uses the same action definitions.

External endpoints

The skill itself makes no network calls. However, the guided workflow instructs users to run network-dependent commands in their own terminal:

CommandEndpointPurpose
`curl -LsSf https://astral.sh/uv/install.sh \sh`astral.shInstall uv package manager
git clone https://github.com/GetSoloTech/solo-cligithub.comInstall solo-cli from source
uv pip install solo-clipypi.orgInstall solo-cli from PyPI
solo data pushhuggingface.coPush recorded dataset (optional)
solo train pushhuggingface.coPush trained model (optional)

Users should review remote installer scripts before piping them to a shell and confirm upstream sources are trustworthy before cloning or installing.

Security & privacy

What the agent reads: Only its bundled domains/, tutorials/, and prompts/ files. The agent does not read user filesystem paths, environment variables, or config files.

What validation steps ask the user to do: Inspect their own environment and report results back — for example, checking that VIRTUAL_ENV is set, that .venv/ exists, that ~/.solo/ was created, or that groups $USER includes dialout. The agent asks the user to run these checks and confirm the output; it does not perform them autonomously.

Credentials: The agent does not read, receive, or store credentials. Optional credentials used by the guided workflow (entered by the user directly in their terminal):

  • HuggingFace token — only if the user pushes datasets or models via solo data push or solo train push
  • Weights & Biases key — only if the user enables wandb_logging during training

Model invocation note

No external AI APIs or models are invoked by the skill. Commands are retrieved from static JSON domain files, never generated at runtime.

Trust statement

All commands presented to users are sourced verbatim from domains/*.json. Nothing is hallucinated or inferred. The constraint field in skill.json enforces this at the manifest level.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.49%
按下载量换算937

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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