Space AI

Starting a session#

1. New session — tick the repositories you are working with (up to five). Only repositories you can see and where AI is enabled are listed.
2. Write a request and pick a model — the list of your keys and your organizations' keys, each with the model from its settings.

Space AI opens from the menu. Ctrl+Enter sends the request. The old /chat address leads here too.

The screen#

• Left — sessions. × next to a session deletes it (this cannot be undone). Sessions of an external agent over MCP are marked MCP.
• Centre — the feed. Your request, the agent's steps as it works — «Collected context», «Reading notes/a.md», «Searching …», «Proposed a change» — the answer and proposal cards. While the agent works, the feed updates by itself, without reloading and without losing your scroll position.
• Right — the session. Attached repositories (× removes one, + Add a repository adds one), what was sent to the model last time and how much of its window is used, money and results: how much was spent, how many turns, how many changes were accepted and what one accepted change cost.
• The model is switched next to the input field — for this session.

On a phone the columns stack: the feed, the session, the list of sessions.

What the agent can do#

The agent is a model with tools, like the Claude, ChatGPT and Copilot agents. It decides itself what to read:

• read — the list of files, a whole file or a part of it, text search, issues and pull requests;
• open issues — an idea, a hypothesis, a problem it found;
• reply in issues and pull requests;
• change issues — title, description, close or reopen, labels;
• write notes into the project context repository — see MCP server;
• propose a change — new or modified files;
• draw images — a PNG proposed into the repository;
• make drills and challenges from a markdown note — see From a note.

Issues, replies and notes are applied at once. File changes only happen when you decide: a card with the files and Accept and Decline buttons appears in the feed. An accepted change becomes an llm/… branch and a pull request — nothing is written to the default branch. When you decline, you can say why: the session remembers it.

The agent reads the project rules — AGENTS.md at the repository root — and the context repository if one is linked. What the agent may do is decided by the owner in Repository settings → AI → Agents.

The agent acts only when asked and only where you have the right: issues where issues are enabled, changes where you have write access. Everything it does is signed «Through Space AI».

What it reads#

Repositories you can see that have AI enabled (Repository settings → AI). Access is checked before every turn and in every action. The text of the fragments goes to the provider of the connected model.

What the agent never sees. List paths in a .skillokignore file at the repository root, one per line, like .gitignore: data/raw/, *.csv, !public.csv. Secrets are closed even without the file: .env (but not .env.example), keys (*.pem, id_rsa), .netrc, .ssh/. A closed path does not show up in the agent's file list or search, cannot be read and cannot be changed by it — the same rule in Space AI, over MCP and in Harness on your computer, where a closed path is hidden from the agent's commands too. The agent reads .skillokignore but never changes it.

Memory#

The model is replaceable; memory stays in SKILLOK: project rules in AGENTS.md, results as notes in the context repository, the session history in its log. Switch the model or the client and nothing is lost.

What it costs#

A turn is several model calls: an initial search, then steps with tools (no more than eight). The price of a turn and of a session is shown in dollars and is paid by the connection — see Connecting models. Limits: 50 turns a day and one turn at a time per session.

Your own agent and automation#

SKILLOK offers the same tools to external agents — Claude, ChatGPT, Cursor, VS Code — over the MCP protocol, connected in one click: MCP server. Requests then go through your subscription, and the agent's changes arrive in Space AI for your decision.

For scripts there is the /api/v1/space/* API with a personal token: sessions, requests, the event log and decisions on proposals, and POST /api/v1/space/repositories creates a repository.

SKILLOK models are also available in the OpenAI format — /api/v1/llm (/models, /chat/completions, streamed answers): this is how the Space AI — Harness desktop app uses them. The same connection pays, within the same limits as a Space AI turn; without a confirmed email AI is closed.

The agent takes challenges with you: start_challenge creates the attempt repository, attempt_status shows the task of the open stage, check_attempt checks the pushed solution and says what failed and why. In the Space AI — Harness desktop app it is one phrase: "commit and check" — commit, push and the check run by themselves.

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