GitHub1s AI

Documentation · Using GitHub1s

GitHub1s AI is the built-in assistant for asking questions about a repository. It can explain attached files or selections and use repository tools to find relevant code. You configure the model endpoint and API key used for each conversation.

Configure a model

1. Click Toggle Secondary Side Bar in the layout controls at the top of GitHub1s to open the AI panel.
2. Click the gear icon at the top of the AI panel, then select Models → Add model.
3. Enter a Name, choose a Provider and, where available, a Protocol.
4. Set the Base URL, API key, and Model ID for an endpoint you can access from your browser.
5. Select Save Model, then click Back to chat.

You can also open the Command Palette (F1) and run GitHub1s AI: Open Chat or GitHub1s AI: Open AI Settings.

The first saved model is selected automatically. With multiple configurations, use the model selector in the chat composer to choose one.

Providers and protocols

Provider	Default protocol	Other supported protocols	Default base URL
Custom	OpenAI Chat Completions	OpenAI Responses, Anthropic Messages	Supply your endpoint
OpenAI	OpenAI Responses	OpenAI Chat Completions	https://api.openai.com/v1
Anthropic	Anthropic Messages	—	https://api.anthropic.com/v1

Use the API base URL, such as https://api.example.com/v1, rather than a complete generation-request URL. The URL must use HTTP or HTTPS and cannot contain credentials, a query string, or a fragment. Use a model ID available through your endpoint.

Browser access

Model requests originate in your browser. The endpoint must support browser requests, including the necessary cross-origin resource sharing (CORS) headers. An endpoint that works from a server-side script may still reject a browser request. Local endpoints can also be affected by the browser's HTTPS and local-network access rules.

Ask questions with context

Start with Repository overview, Explain current file, or Explain selection, or type a question in the chat composer.

Use the composer toolbar's Add file…, Attach current file, or Attach current selection buttons. The editor action Add to GitHub1s AI Chat attaches the selection when one exists, or the current file otherwise.

Attached content is read when you send the message. Remove a pending attachment with its remove button before sending. Click an attachment chip to open its source file or selection.

Include recent files is enabled by default. It adds up to five recently viewed file paths to the model's context; the assistant can then read those files with its tools. Turn it off in the composer when those paths are not relevant to the question.

New Chat starts a separate conversation and clears pending attachments. Previous conversations remain available through GitHub1s AI: Show History.

Customize responses

In AI Settings → Prompts, add preferences such as the response language under User Rules, then select Save prompts. Instructions replaces the default assistant instructions, and Quick Actions customizes the starter questions. Leave instruction or quick-action fields empty to use their defaults. Reset updates the form; select Save prompts to save the reset values.

Repository tools

The assistant has four built-in tools:

Tool	Purpose
read	Read a text file or a range of lines
ls	List a directory
glob	Find files by a path pattern
search	Search text in files

These tools read within the open workspace. Results are bounded: for example, read accepts files up to 5 MiB and returns at most 2,000 lines per call. Long lines and tool output can be truncated, and searches depend on the workspace's search provider. These are tool limits; attached files use a separate context-loading path.

For a large repository, ask about a specific directory, file, or symbol so the assistant can retrieve focused context.

Connect MCP servers

Model Context Protocol (MCP) servers add tools to the chat. Open GitHub1s AI: Open AI Settings, select MCP, and enter a configuration such as:

{
	"mcpServers": {
		"example": {
			"type": "http",
			"url": "https://example.com/mcp",
			"headers": {
				"Authorization": "Bearer YOUR_TOKEN"
			}
		}
	}
}

Replace the example URL and token, then select Save MCP settings. Changes apply to the next response. Supported transports are http and sse; local stdio servers are unavailable in the browser. Headers are optional, and the server must allow browser access.

Configured MCP tools become available to the assistant. Their capabilities determine which external actions it can perform; they are not restricted by the built-in repository tools' read-only behavior. Connect servers whose tools you intend the assistant to use.

Save { "mcpServers": {} } to remove all configured MCP connections.

Data and storage

Data	Where it goes
Model configuration, including API keys	Saved in browser-backed VS Code extension global state; the selected credentials are used for model requests
Messages, attached code, recent file paths, and retrieved tool results	Included in requests to the configured model endpoint as conversation context
Conversation history	Saved in browser-backed extension storage, separated by workspace
MCP configuration and credentials	Saved in extension global state; used to connect to the configured servers
MCP tool calls	Sent to the corresponding server; their results become available to the model

The model and MCP services receive the data sent to them under their own service policies. Select endpoints appropriate for the repository content you plan to discuss.

Manage saved data

• Delete one conversation: open Show History, use its delete action, and confirm Delete.
• Export conversations: in AI Settings, open General → Export history → Export. The JSON contains conversation data for the current workspace, including stored message and tool content.
• Reset AI data: in General, select Clear all data and confirm. This removes local AI conversations across all workspaces, model settings and API keys, MCP settings, and prompt settings.

Troubleshooting

Message or symptom	What to check
Select a model before sending a message.	Add a model and select it in the composer
Authentication failure	Check the API key and the endpoint account's access
Endpoint or model not found	Check the base URL, protocol, and model ID
Unable to reach the endpoint	Check network access, CORS, and browser restrictions on the endpoint
Rate limit reached	Follow the model service's retry guidance
Missing repository context	Attach the relevant file or selection; check whether repository search is available
Unable to load MCP tools	Check the server URL, credentials, CORS support, and tool-name conflicts