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Copilot Spaces

OrganizationPopular
github
copilot-spaces

Use Copilot Spaces to provide project-specific context to conversations. Use this skill when users mention a "Copilot space", want to load context from a shared knowledge base, discover available spaces, or ask questions grounded in curated project documentation, code, and instructions.

Overview

Publishergithub
Repositoryawesome-copilot
Skill namecopilot-spaces
Stars
39.6K
Forks
5K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by github on GitHub. Read the source before you install it.

Installation

Install the Copilot Spaces AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/github/awesome-copilot/tree/main/skills/copilot-spaces
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/copilot-spaces .claude/skills/copilot-spaces
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Copilot Spaces in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Copilot Spaces on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Copilot Spaces is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Copilot Spaces

Use Copilot Spaces to bring curated, project-specific context into conversations. A Space is a shared collection of repositories, files, documentation, and instructions that grounds Copilot responses in your team's actual code and knowledge.

Available Tools

MCP Tools (Read-only)

ToolPurpose
mcp__github__list_copilot_spacesList all spaces accessible to the current user
mcp__github__get_copilot_spaceLoad a space's full context by owner and name

REST API via gh api (Full CRUD)

The Spaces REST API supports creating, updating, deleting spaces, and managing collaborators. The MCP server only exposes read operations, so use gh api for writes.

User Spaces:

MethodEndpointPurpose
POST/users/{username}/copilot-spacesCreate a space
GET/users/{username}/copilot-spacesList spaces
GET/users/{username}/copilot-spaces/{number}Get a space
PUT/users/{username}/copilot-spaces/{number}Update a space
DELETE/users/{username}/copilot-spaces/{number}Delete a space

Organization Spaces: Same pattern under /orgs/{org}/copilot-spaces/...

Collaborators: Add, list, update, and remove collaborators at .../collaborators

Scope requirements: PAT needs read:user for reads, user for writes. Add with gh auth refresh -h github.com -s user.

Note: This API is functional but not yet in the public REST API docs. It may require the copilot_spaces_api feature flag.

When to Use Spaces

  • User mentions "Copilot space" or asks to "load a space"
  • User wants answers grounded in specific project docs, code, or standards
  • User asks "what spaces are available?" or "find a space for X"
  • User needs onboarding context, architecture docs, or team-specific guidance
  • User wants to follow a structured workflow defined in a Space (templates, checklists, multi-step processes)

Workflow

1. Discover Spaces

When a user asks what spaces are available or you need to find the right space:

Call mcp__github__list_copilot_spaces

This returns all spaces the user can access, each with a name and owner_login. Present relevant matches to the user.

To filter for a specific user's spaces, match owner_login against the username (e.g., "show me my spaces").

2. Load a Space

When a user names a specific space or you've identified the right one:

Call mcp__github__get_copilot_space with:
  owner: "org-or-user"    (the owner_login from the list)
  name: "Space Name"      (exact space name, case-sensitive)

This returns the space's full content: attached documentation, code context, custom instructions, and any other curated materials. Use this context to inform your responses.

3. Follow the Breadcrumbs

Space content often references external resources: GitHub issues, dashboards, repos, discussions, or other tools. Proactively fetch these using other MCP tools to gather complete context. For example:

  • A space references an initiative tracking issue. Use issue_read to get the latest comments.
  • A space links to a project board. Use project tools to check current status.
  • A space mentions a repo's masterplan. Use get_file_contents to read it.

4. Answer or Execute

Once loaded, use the space content based on what it contains:

If the space contains reference material (docs, code, standards):

  • Answer questions about the project's architecture, patterns, or standards
  • Generate code that follows the team's conventions
  • Debug issues using project-specific knowledge

If the space contains workflow instructions (templates, step-by-step processes):

  • Follow the workflow as defined, step by step
  • Gather data from the sources the workflow specifies
  • Produce output in the format the workflow defines
  • Show progress after each step so the user can steer

5. Manage Spaces (via gh api)

When a user wants to create, update, or delete a space, use gh api. First, find the space number from the list endpoint.

Update a space's instructions:

bash
gh api users/{username}/copilot-spaces/{number} \
  -X PUT \
  -f general_instructions="New instructions here"

Update name, description, or instructions together:

bash
gh api users/{username}/copilot-spaces/{number} \
  -X PUT \
  -f name="Updated Name" \
  -f description="Updated description" \
  -f general_instructions="Updated instructions"

Create a new space:

bash
gh api users/{username}/copilot-spaces \
  -X POST \
  -f name="My New Space" \
  -f general_instructions="Help me with..." \
  -f visibility="private"

Attach resources (replaces entire resource list):

json
{
  "resources_attributes": [
    { "resource_type": "free_text", "metadata": { "name": "Notes", "text": "Content here" } },
    { "resource_type": "github_issue", "metadata": { "repository_id": 12345, "number": 42 } },
    { "resource_type": "github_file", "metadata": { "repository_id": 12345, "file_path": "docs/guide.md" } }
  ]
}

Delete a space:

bash
gh api users/{username}/copilot-spaces/{number} -X DELETE

Updatable fields: name, description, general_instructions, icon_type, icon_color, visibility ("private"/"public"), base_role ("no_access"/"reader"), resources_attributes

Examples

Example 1: User Asks for a Space

User: "Load the Accessibility copilot space"

Action:

  1. Call mcp__github__get_copilot_space with owner "github", name "Accessibility"
  2. Use the returned context to answer questions about accessibility standards, MAS grades, compliance processes, etc.

Example 2: User Wants to Find Spaces

User: "What copilot spaces are available for our team?"

Action:

  1. Call mcp__github__list_copilot_spaces
  2. Filter/present spaces relevant to the user's org or interests
  3. Offer to load any space they're interested in

Example 3: Context-Grounded Question

User: "Using the security space, what's our policy on secret scanning?"

Action:

  1. Call mcp__github__get_copilot_space with the appropriate owner and name
  2. Find the relevant policy in the space content
  3. Answer based on the actual internal documentation

Example 4: Space as a Workflow Engine

User: "Write my weekly update using the PM Weekly Updates space"

Action:

  1. Call mcp__github__get_copilot_space to load the space. It contains a template format and step-by-step instructions.
  2. Follow the space's workflow: pull data from attached initiative issues, gather metrics, draft each section.
  3. Fetch external resources referenced by the space (tracking issues, dashboards) using other MCP tools.
  4. Show the draft after each section so the user can review and fill in gaps.
  5. Produce the final output in the format the space defines.

Example 5: Update Space Instructions Programmatically

User: "Update my PM Weekly Updates space to include a new writing guideline"

Action:

  1. Call mcp__github__list_copilot_spaces and find the space number (e.g., 19).
  2. Call mcp__github__get_copilot_space to read current instructions.
  3. Modify the instructions text as requested.
  4. Push the update:
bash
gh api users/labudis/copilot-spaces/19 -X PUT -f general_instructions="updated instructions..."

Tips

  • Space names are case-sensitive. Use the exact name from list_copilot_spaces.
  • Spaces can be owned by users or organizations. Always provide both owner and name.
  • Space content can be large (20KB+). If returned as a temp file, use grep or view_range to find relevant sections rather than reading everything at once.
  • If a space isn't found, suggest listing available spaces to find the right name.
  • Spaces auto-update as underlying repos change, so the context is always current.
  • Some spaces contain custom instructions that should guide your behavior (coding standards, preferred patterns, workflows). Treat these as directives, not suggestions.
  • Write operations (gh api for create/update/delete) require the user PAT scope. If you get a 404 on write operations, run gh auth refresh -h github.com -s user.
  • Resource updates replace the entire array. To add a resource, include all existing resources plus the new one. To remove one, include { "id": 123, "_destroy": true } in the array.

Frequently asked questions

What does the Copilot Spaces AI skill do?

Use Copilot Spaces to provide project-specific context to conversations. Use this skill when users mention a "Copilot space", want to load context from a shared knowledge base, discover available spaces, or ask questions grounded in curated project documentation, code, and instructions.

Why use Copilot Spaces on TypingMind?

Because you install it once and use it with any model. Copilot Spaces is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Copilot Spaces in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/copilot-spaces. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Copilot Spaces?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Copilot Spaces?

As many as you like. As long as a model supports skills, you can use Copilot Spaces with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Copilot Spaces AI skill free?

Yes. It is published on GitHub by github under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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