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#

SkillTypeStatussolo_cli_guideguideAvailablesolo_hub_guideguideThis skillsolo_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:

EndpointPurposehub.getsolo.techAll Hub UI interactionshuggingface.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.