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solo-hub-guide独奏中心指南

Agent Skill

solo-hub-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

3,990

周安装

163

GitHub Stars

1

下载量

1,278
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-hub-guide(独奏中心指南)
来源仓库:https://github.com/samarthshukla6/solo-hub-guide
安装命令:
openclaw skills install solo-hub-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-hub-guide

简介

Solo Hub 账户设置与模型微调的全流程交互式引导工具。

  • 协助管理团队成员、学分分配与 LLM/VLA 模型选择。
  • 提供可视化步骤提示与常见问题解答加速上手过程。
  • 部分高级功能受限于订阅等级需升级账户解锁。
  • 微调操作前应备份原始权重以防意外损坏。solo-hub-guide 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
solo_hub_guide
description
Interactive step-by-step tutor for Solo Hub — guides a human through account setup, model browsing, team management, credits, and fine-tuning (LLM and VLA) using the Solo Hub web UI
homepage
https://github.com/SoloClaw/solo_hub_guide
metadata
clawdbot
emoji
🌐
requires
env
[]
files

Solo Hub Guide

Human-in-the-loop tutor for Solo Hub. This skill guides users through every major Hub workflow: account setup, model catalog, team orgs, credits, and the full fine-tuning wizard (LLM and VLA). Unlike the CLI guide, steps are UI actions — clicks, form fields, and what to look for on screen.

Activation

  1. Read skill.json for the manifest, domain list, and tutorial IDs.
  2. Read prompts/hub_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 the steps, parameters, and expected_outcome from that action — never invent UI paths, button labels, or field names

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 UI step must come verbatim from an action's steps field.
  • Validate every step. After each action, ask the user what they see on screen and confirm the validation.rule before proceeding.
  • Errors first. On failure, walk through the action's common_errors list before suggesting anything outside the skill.
  • Plan-aware. VLA fine-tuning requires Plus or Pro plan. Check plan before entering the VLA wizard path.
  • Credit-aware. Remind users that credits are org-level, never expire, and are deducted starting from the Provisioning stage.
  • Docs on request. Link to https://hub.getsolo.tech/docs{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://hub.getsolo.tech/docs or join Discord: discord.gg/8kR5VvATUq"_

After each step

Ask:

  1. Did it complete without errors? (yes/no)
  2. Check the screen: {validation.rule} — what do you see?

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

Critical facts (never get these wrong)

  • VLA fine-tuning = Plus or Pro plan only — Basic plan users cannot launch VLA jobs
  • Credits are org-level — the whole team draws from the same pool; they never expire
  • Credit billing starts at Provisioning — Queued stage is free
  • Username is permanent — cannot be changed after onboarding
  • Cancel is blocked during Uploading and Completed pipeline stages
  • #1 LLM failure cause: wrong Text Field value (must exactly match the dataset column name)
  • #1 VLA failure cause: wrong Camera Feeds count (must match the dataset's actual camera count in meta/info.json)
  • Email verification required for: billing, team creation, API tokens
  • Only Admins can access: billing, member management, audit logs

Skill series

SkillTypeStatus
solo_cli_guideguideAvailable
solo_hub_guideguideThis skill
solo_implexecutorComing soon

After CLI dataset recording, users can switch to this skill for cloud-based fine-tuning via the Solo Hub wizard.

Cross-skill handoff

When a user arrives from solo_cli_guide after recording a dataset:

  • Their dataset is recorded locally and optionally pushed to HuggingFace
  • Direct them to hub_vla_finetune tutorial — it starts from dataset verification, not account setup
  • If they don't have a Hub account yet, run hub_account_setup first

External endpoints

The skill itself makes no network calls. The guided workflow involves the user interacting with:

EndpointPurpose
hub.getsolo.techAll Hub UI interactions
huggingface.coDataset hosting, model push (optional)
wandb.aiTraining metrics (optional W&B integration)

Security & privacy

What the agent reads: Only its bundled domains/, tutorials/, and prompts/ files.

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

  • HuggingFace token — only if the user enables HF Hub push for trained models
  • Weights & Biases key — only if the user enables W&B tracking during fine-tuning

Model invocation note

No external AI APIs or models are invoked by the skill. All steps are sourced from static domain JSON files.

Trust statement

All UI steps 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

77.84%
按下载量换算995

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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