Plan Canvas

作者 affaan-mef648e01899bMIT275K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫3 天前更新

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.

AI 產生的概覽

在本地瀏覽器畫布中開啟計畫或 HTML 產物,供人工標註、聊天並給出核准或要求修改的結論。

功能
此技能執行一個 CLI 加 JSON 的審閱迴圈:在本地回送瀏覽器畫布中開啟 Markdown 或 HTML 產物,人工可標註特定元素、聊天,並給出核准或要求修改的結論。代理會阻塞在 await 指令上,以 JSON 形式取得回饋,在畫布內回覆,並透過編輯產物檔案進行修改,因為畫布會在儲存時即時重新載入。它也會在計畫中渲染 Mermaid 圖表區塊,並在審閱結束時關閉工作階段。
適用情境
適用於提交計畫產物以取得確認,或審閱設計、比較與報告,且直接指向某個元素比打字回饋更方便的情境。僅適用於本地 .md 或 .html 產物,不適用於程式碼差異、執行網頁應用程式或遠端 URL。
執行需求
需要 ecc-universal 套件提供的 ecc-plan-canvas 命令列工具(或以 Node 執行外掛的 plan-canvas.js)、本地瀏覽器,以及 127.0.0.1:4517 上的回送伺服器。Mermaid 圖表預設從固定 CDN 載入,除非設定本地鏡像;此技能不附帶指令碼。

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 workecc-plan-canvas typing <file> --state thinking# switch to "agent is typing..." just before a reply landsecc-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>.

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
```mermaidflowchart 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.mdecc-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.

來源與署名

來源:affaan-m/ecc位於.agents/skills/plan-canvas提交ef648e0

授權條款: MIT

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

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