跳到正文
cccskills
免费在 GitHub 公开中文介绍

plan-canvas

在浏览器中打开本地计划书或HTML文件,通过针对具体内容的批注和聊天接收批准或修改请求。保存文件后页面会更新,可在同一页面继续审阅。

原文查看原文说明

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 评分100分/ 100查看安装方法

适用场景

  • 审阅并批准实施计划
  • 指出设计中需要修改的位置
  • 为报告和比较资料添加批注
  • 在同一页面确认修改结果

中文介绍

功能

在浏览器中展示本地Markdown计划书或HTML文件,通过批注和聊天进行审阅。使用者可指定需要修改的元素或文字,发送批准或修改请求。代理以JSON格式接收反馈,并在同一页面回复。编辑文件并保存后,页面随之更新,也可查看使用Mermaid编写的图表。

适用场景

适合获取实施计划的批准,或围绕设计、比较资料、报告的具体位置展开讨论。“把这一部分移过去”“修改这段说明”等意见可以直接关联到目标内容。修改后,仍可在同一页面继续检查。

使用示例

  • “在浏览器中打开这份计划书,接收批准或修改请求。”
  • “让这份HTML文件支持带批注的审阅。”
  • “根据反馈修改资料,并在页面内回复。”

注意事项

使用ecc-universal附带的ecc-plan-canvas。仅支持本地.md和.html文件,不适用于远程URL、运行中的网页应用或代码差异审查。Mermaid从CDN加载,离线时显示图表源码。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

客观评估

AI 仅根据 SKILL.md 的内容,从 4 个方面进行了评估。星标数和热度不计入评估。

指令清晰度能否看出何时使用、做什么
A良好明确说明计划批准和资料批注的用途,并列出不适用的审查类型。
步骤具体性步骤、输入输出和示例是否具体
A良好提供open、await、回复和end步骤,以及返回JSON的示例。
安全性发送数据、删除文件、执行命令等是否有说明
A良好说明仅本机可访问的服务器和CDN加载,并规定批准后实施及重新打开条件。
安装难易度所需工具和 API 密钥是否少且有说明
A良好说明无需额外依赖,并提供ecc-universal所附命令行工具的启动方式。

总分按每项 A=25 分、B=15 分、C=5 分相加。 由 AI(OpenAI Codex)于 2026年10月19日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

包含的文件(1)

  • SKILL.md8.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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.

# 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:

{
  "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:

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:

# 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>.

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.

```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:

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:

# 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.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

accessibility

免费有简介AI 评分 100分

依据WCAG 2.2设计和检查Web、iOS及Android界面,核查读屏标签、键盘操作、配色对比度和操作目标尺寸,使界面支持辅助技术。

  • 为纯图标按钮添加说明
  • 检查键盘操作与模态框焦点
  • 检查对比度与操作目标尺寸
affaan-m/ECC28.4万2026年10月16日 更新

agent-architecture-audit

免费有简介AI 评分 80分

从指令、记忆、工具执行和界面显示等十二个层面排查人工智能代理故障,依据代码和日志梳理原因,按严重程度列出问题并提出修复方案。

  • 排查仅在应用内出现的故障
  • 调查旧对话混入回答的原因
  • 核对工具漏执行或虚报执行
affaan-m/ECC28.4万2026年10月16日 更新

agent-eval

免费有简介AI 评分 80分

用实际开发任务比较多个编程智能体,记录成功率、可获取的API费用、耗时和重复运行的稳定性,为工具选型及更新后的性能评估提供数据。

  • 用实际开发任务比较智能体
  • 采用新工具或模型前进行评估
  • 检查智能体更新后的性能
affaan-m/ECC28.4万2026年10月16日 更新

agent-harness-construction

免费有简介AI 评分 100分

设计和调整AI智能体使用的工具、输入与返回格式,明确出错后的恢复、重试和停止条件,管理上下文信息量,并以完成率、重试次数和成功任务成本评估改进。

  • 设计智能体工具及输入格式
  • 明确工具结果与下一步行动
  • 制定安全重试与停止条件
affaan-m/ECC28.4万2026年10月16日 更新

agent-introspection-debugging

免费有简介AI 评分 100分

根据错误信息和执行环境,分析AI代理反复失败或重复操作的原因。通过小范围、可撤销的恢复操作检验假设,并将结果与依据整理成可供交接的报告。

  • 诊断代理连续失败
  • 调查重复调用工具的循环
  • 检查上下文积累导致的输出退化
affaan-m/ECC28.4万2026年10月5日 更新

agent-introspection-debugging

免费有简介AI 评分 100分

在AI代理反复失败或重复操作时,记录错误与环境前提、排查原因,采取影响有限的恢复操作,并汇总结果和证据,为有依据的重试与交接提供支持。

  • 排查重复调用工具的原因
  • 调查对话膨胀导致的质量下降
  • 核对文件路径与环境差异
affaan-m/ECC28.4万2026年10月16日 更新

查看 affaan-m 的全部技能

报告此技能的问题