create-canvas

A guide for creating canvas extensions that open interactive content in GitHub Copilot's side panel. A canvas is a rendered view that can receive inputs and actions through the Copilot runtime.

In plain words
What is it for?
Use it to create, review, or debug canvas actions, inputs, rendered content, and extension wiring.
Why use it?
It helps connect the extension to the correct runtime lifecycle and prevents confusion about where canvas registration and event handling happen.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/github/gh-aw/create-canvas
Any agent
npx skills add github/gh-aw --skill create-canvas
Clone the repo
git clone --depth 1 https://github.com/github/gh-aw

Made for: Claude Code, Codex.

Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,549 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00061 $0.03549
Opus 5 $0.00030 $0.01775
Sonnet 5 $0.00012 $0.00710
Haiku 4.5 $0.00006 $0.00355

Measured yesterday against content hash d8b3307a7d48, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

create-canvas scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/skills/create-canvas/SKILL.md · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Extension Canvas Authoring

Use this skill when creating or debugging an extension canvas that integrates with the runtime canvas model.

The host app no longer participates in extension canvas registration. Extensions declare canvases directly to the runtime via the Copilot SDK on joinSession; the runtime routes provider callbacks (canvas.open, canvas.action.invoke, etc.) straight to the declaring connection; the host app just renders whatever URL the provider returns.

Authoring workflow (do this in order)

  1. Decide the scope. Project (.github/extensions/<name>/) is committed to the repo and shared with the team. User ($COPILOT_HOME/extensions/<name>/) is local to the current user. Session ($COPILOT_HOME/session-state/<sessionId>/extensions/<name>/) is loaded only for the current session — ideal for a throwaway canvas for one conversation. Unless the request makes it obvious, ask before creating files — the choice changes who sees the extension, whether it's committed, and the resulting extensionId.

  2. Scaffold via tool, don't hand-write the skeleton.

    extensions_manage({ operation: "scaffold", kind: "canvas", name: "<name>", location: "project" | "user" | "session" })
    

    The canvas scaffold produces an extension.mjs with joinSession({ canvases: [createCanvas({...})] }), a working loopback HTTP server per instance, an example action, and onClose cleanup. Edit from there.

  3. Edit the file. Implement your open, actions[], optional onClose, and (if needed) tools/hooks alongside.

  4. Reload. Call extensions_reload. Stale canvas instances flip to stale, then back to ready once the provider reconnects.

  5. Verify. Call extensions_manage({ operation: "list" }) and extensions_manage({ operation: "inspect", name: "<name>" }). If the extension is marked failed, inspect surfaces the log file path and a tail — that log is the primary debugging surface.

  6. Drive it. Run the validation checklist below via list_canvas_capabilities, open_canvas, and invoke_canvas_action.

Read the full file on GitHub · 260 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 260 lines · 61 tokens per session scan A d8b3307a7d48

Subscribe to this mod's changes

create-canvas is a skill published in the GitHub repository github/gh-aw (5,050 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 3,549 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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