Agent skill

Plan Canvas

by affaan-m in affaan-m/ECC

Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page.

MITAuto-check passedFrontend & Design

Install Plan Canvas

skills CLI
$ npx skills add affaan-m/ECC --skill plan-canvas -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC plan-canvas --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/plan-canvas .claude/skills/plan-canvas && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
plan-canvas
GitHub stars
277k
Used in
1 other repo
Token cost
~2.2k tokens
SKILL.md length
1,001 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page.

  • Presenting a plan for review
  • SKILL.md covers When to Use, How It Works, Diagrams (Mermaid) and Rules, plus 2 more sections
  • Calls node
  • Feedback like move this

What it does

Plan Canvas is an agent skill from affaan-m/ECC. Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or when feedback like "move this, change that" is easier pointed at than typed.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Frontend & Design, covering HTML artifacts. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • Presenting a plan for review
  • Feedback like move this
  • Change that is easier pointed at than typed

Example prompts

  • “move this, change that”
  • “/plan-canvas”

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Plan Canvas loads about 2.2k tokens when it runs. Until then it costs about 72 tokens; SKILL.md has 1,001 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 1,001 words, ~2,159 tokens.

Download SKILL.mdSave it as .claude/skills/plan-canvas/SKILL.md (or your agent's skills folder).
name
plan-canvas
description
Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or when feedback like "move this, change that" is easier pointed at than typed.
metadata.version
1.0.0
metadata.origin
ECC

Plan Canvas

Review loop for plans and visual artifacts: you write the artifact, the human reviews it in the browser — annotating the exact element they mean, chatting, and delivering an Approve plan / Request changes verdict — while you block on a single CLI call that returns their feedback as JSON.

Inspired by lavish-axi; rebuilt ECC-native around the /plan confirmation gate, with zero dependencies.

When to Use

  • You just wrote a plan artifact (.claude/plans/*.plan.md from /plan) and need the CONFIRM/approve decision — the canvas verdict replaces a typed "yes/proceed".
  • The user should point at what to change: reviewing designs, comparisons, reports, or any local .md / .html artifact.
  • The user asks for /plan-canvas, a visual review, or "open it in the browser".

Do NOT use for: code review of diffs (/code-review), running web apps, or remote URLs. The canvas serves local artifact files only.

How It Works

Invoke the CLI as ecc-plan-canvas — the bin shipped by the ecc-universal package (on PATH after a global/plugin install; node "$CLAUDE_PLUGIN_ROOT/scripts/plan-canvas.js" also works for plugin installs). Run it from the project you are reviewing in; it works from any working directory. It manages a detached loopback server (127.0.0.1:4517) shared by all sessions, keyed by artifact path — no session ids to track.

The workflow is a plain CLI-plus-JSON loop, so it is model- and harness-agnostic: any agent that can run a shell command and read stdout drives it the same way (Claude Code, Codex, Cursor, Gemini, OpenCode, Copilot). Trigger it however your harness surfaces skills — e.g. /plan-canvas in Claude Code, $plan-canvas in Codex — or just run the ecc-plan-canvas commands directly.

bash
# 1. Open the artifact in the user's browser (returns immediately)
ecc-plan-canvas open .claude/plans/feature.plan.md

# 2. Block until the human responds. Leave running; re-run if interrupted:
#    queued feedback is never lost.
ecc-plan-canvas await .claude/plans/feature.plan.md
Stay listening, or the human talks to an empty chair

Feedback only reaches you while an await is actually parked on the session. If your turn ends with nothing listening, the message sits in the queue and, from the human's side of the glass, sending appears to do nothing at all.

So run await as a background task when your harness supports one (in Claude Code, a Bash call with run_in_background: true). It exits the moment feedback arrives and the harness hands you the JSON, which keeps the loop alive across turns instead of dying with the foreground call. A foreground await works too, but only until the harness time-limits it.

Two backstops exist, and neither is an excuse to skip the above:

  • ecc-plan-canvas pending lists feedback queued with no listener. Check it whenever you are unsure whether you missed something.
  • The stop:plan-canvas-pending hook blocks your turn from ending while canvas feedback is undelivered, and hands you the messages. If you are reading feedback from that hook, you stopped listening too early.

await prints JSON when the human acts:

json
{
  "status": "feedback",
  "items": [
    { "kind": "annotation", "text": "Split this into two phases",
      "anchor": { "selector": "h2:nth-of-type(3)", "tag": "h2", "snippet": "Phase 2: Migration" } },
    { "kind": "verdict", "verdict": "request-changes" }
  ]
}
  • kind: "chat" — freeform message; answer in the canvas, not the terminal.
  • kind: "annotation" — feedback anchored to an element (anchor.selector, anchor.snippet show what they pointed at; anchor.textRange.text when they highlighted a passage).
  • kind: "verdict" — approve means the plan is CONFIRMED: stop polling, end the session, and start implementing. request-changes means revise the artifact (the canvas live-reloads it) and keep the loop going.

3. Always respond in the canvas, then keep listening. One command does both:

bash
ecc-plan-canvas await <file> --reply "Split Phase 2 as requested. Take a look."

Every human message gets a reply in the canvas, even a one-liner like "On it, rewriting the risk table now." Silence in the chat panel is indistinguishable from a broken canvas, which is exactly the failure this loop exists to prevent. Answer there, not only in the terminal.

While you work, keep the chat honest with the activity indicator:

bash
# animated "agent is thinking..." bubble; refresh it during long work
ecc-plan-canvas typing <file> --state thinking
# switch to "agent is typing..." just before a reply lands
ecc-plan-canvas typing <file> --state typing

await sets thinking for you the moment it hands you a batch, and --reply clears it. Both states self-expire, so a crashed agent decays to an honest "queued" instead of leaving the human watching dots forever. Refresh thinking if a revision takes more than a minute.

4. End when review concludes: ecc-plan-canvas end <file>.

Show full SKILL.md (374 more words)Show less

Diagrams (Mermaid)

When part of the plan is a flow, architecture, sequence, state machine, ER model, or dependency graph, author it as a fenced ```mermaid block instead of ASCII art or a wall of prose — the canvas renders it as a themed diagram the human can point at. Reach for it when a picture reads faster than a paragraph; skip it for simple lists or tables.

markdown
```mermaid
flowchart LR
  A[Market resolves] --> B{Watchers?}
  B -->|yes| C[Enqueue jobs] --> D[Fan-out worker]
```

Diagrams render in the ECC dark theme with the accent palette. Mermaid loads in the browser from a pinned CDN; if that is unavailable (offline), the block degrades to showing its source, so the review is never blocked. Point a local mirror at ECC_PLAN_CANVAS_MERMAID_URL for air-gapped use.

Rules

  • Markdown artifacts render in ECC's plan template (including Mermaid blocks); .html artifacts render as-is with the annotation layer injected. For HTML authoring guidance use the frontend-design-direction and artifact-design skills.
  • Edit the artifact file to revise — the canvas live-reloads on save. Never re-run open to refresh.
  • {"status": "ended", "endedBy": "user"} (or sessionEnded: true on a feedback batch) means the user closed the review: stop polling, deliver remaining updates in chat, and do not reopen. A plain open on that session is refused; pass --reopen only when the user asks to resume.
  • Sibling assets (images, CSS) must sit next to the artifact and be referenced by relative path.
  • The server is loopback-only and exits after 30 idle minutes (ECC_PLAN_CANVAS_IDLE_MS); stop shuts it down explicitly. State lives in ~/.claude/plan-canvas/ (ECC_PLAN_CANVAS_STATE_DIR).

Examples

Plan approval flow — /plan writes .claude/plans/notifications.plan.md and must WAIT for confirmation:

bash
ecc-plan-canvas open .claude/plans/notifications.plan.md
ecc-plan-canvas await .claude/plans/notifications.plan.md
# → {"status":"feedback","items":[{"kind":"verdict","verdict":"approve"}]}
ecc-plan-canvas end .claude/plans/notifications.plan.md
# plan is confirmed — begin implementation

Revision loop — feedback arrives, you edit the file, reply, keep listening:

bash
# await returned annotations → edit the .plan.md (canvas live-reloads)
ecc-plan-canvas await <file> --reply "Reworked the risk table."
# → blocks again until the next response

Anti-Patterns

  • Polling with --timeout-ms in a loop. It exists for tests. Leave the plain await running instead.
  • Ending your turn with no await listening while the review is still open. That is the one failure the human experiences as "I sent a message and nothing happened".
  • Reading the feedback but answering only in the terminal. The human is looking at the canvas.
  • Reopening after a user-initiated end "just to show" something.
  • Pasting the whole plan into chat and opening a canvas — pick the canvas and keep the terminal summary to one line.
  • Parsing the canvas chat from state files — everything you need arrives via await.

Design notes and origin: docs/design/plan-canvas.md.

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/plan-canvas of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 9, 2026.

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Questions about Plan Canvas

What does Plan Canvas do?

Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Plan Canvas is an agent skill from affaan-m/ECC. Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page.

When should I use Plan Canvas?

Plan Canvas fits situations like: presenting a plan for review; feedback like move this; change that is easier pointed at than typed.

How do I install Plan Canvas in Claude Code?

Run `npx skills add affaan-m/ECC --skill plan-canvas -a claude-code`. Or copy the skill folder (skills/plan-canvas in affaan-m/ECC) into .claude/skills/plan-canvas in your project. Claude Code loads it when a task matches its description.

How do I install Plan Canvas in Codex?

Run `npx skills add affaan-m/ECC --skill plan-canvas -a codex`. Or copy the skill folder (skills/plan-canvas in affaan-m/ECC) into .agents/skills/plan-canvas in your project. Codex loads it when a task matches its description.

Can I use Plan Canvas in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill plan-canvas -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/plan-canvas, .gemini/skills/plan-canvas, .github/skills/plan-canvas and .opencode/skills/plan-canvas in your project.

What does Plan Canvas need to run?

Going by SKILL.md and its folder, Plan Canvas needs the command-line tools its instructions call (node).

Does Plan Canvas access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Plan Canvas safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Plan Canvas use?

Plan Canvas is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Plan Canvas use?

About 2.2k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Plan Canvas?

Skills that share tags, products or a category with Plan Canvas: LobeHub Interactive Prototype (lobehub/lobehub, 83k stars), Paperclip Page (paperclipai/paperclip, 100k stars), Openkb Deck Neon (VectifyAI/OpenKB, 4.8k stars) and Webhome Homepage Builder (webhtv/webhtv, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Plan Canvas?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.