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Agent Skill · 研究检索

ce-demo-reel(CE 演示卷轴)

ce-demo-reel 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

ce-demo-reel 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 27,985。

总安装 3,295周安装 132GitHub Stars 15,913下载 1,067核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ce-demo-reel(CE 演示卷轴)
来源仓库:https://github.com/everyinc/compound-engineering-plugin
仓库路径:skills/ce-demo-reel
安装命令:
npx skills add https://github.com/everyinc/compound-engineering-plugin --skill ce-demo-reel
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/everyinc/compound-engineering-plugin --skill ce-demo-reel

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。可结合关键词、任务场景或来源线索进行信息定位,支持项目类型识别与证据录制建议。需确认权限范围和维护状态,避免触发联网或文件读写操作,注意区分测试输出与真实产品使用。

安装前建议检查原始 README 和仓库路径,确保符合宿主环境要求。ce-demo-reel 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ce-demo-reel

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/everyinc/compound-engineering-plugin --skill c…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ce-demo-reel 怎么安装?

在终端执行 npx skills add https://github.com/everyinc/compound-engineering-plugin --skill ce-demo-ree…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ce-demo-reel 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ce-demo-reel 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

ce-demo-reel 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

ce-demo-reel 用的人多吗?

公开数据是累计安装 3,295 次,近一周安装 132 次,下载 1,067 次,GitHub 15,913 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ce-demo-reel 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 15,913 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ce-demo-reel

CE 演示卷轴 · 本页

3,29515,913操作浏览器未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Demo Reel

Detect project type, recommend a capture tier, record visual evidence, upload to a public URL, and return markdown for PR inclusion.

Evidence means USING THE PRODUCT, not running tests. "I ran npm test" is test evidence. Evidence capture is running the actual CLI command, opening the web app, making the API call, or triggering the feature. The distinction is absolute -- test output is never labeled "Demo" or "Screenshots."

If real product usage is impractical (requires API keys, cloud deploy, paid services, bot tokens), say so explicitly: "Real evidence would require [X]. Recommending [fallback approach] instead." Do not silently skip to "no evidence needed" or substitute test output.

Never generate fake or placeholder image/GIF URLs. If upload fails, report the failure.

Never Record Secrets

Recordings must never contain credentials — not in commands, output, URL bars, or on-screen UI. If the demo needs a credential, set it before the recording starts, outside the recorded region.

Core principle: secrets should affect the environment, not the visible transcript. Hidden *real* setup beats visible *fake* setup — fake setup breaks the demo and still leaks the secret's shape.

  • Plan it out of frame. Route every surface where a secret could appear (env exports, CLI flag values, command output, auth headers, URL params, DevTools, config pages) out of the recorded region. Use VHS Hide/Show; invoke CLIs via env vars, not secret flag values; stay on user-facing pages. Show the authenticated result, not the auth step.
  • Do not substitute placeholders inside the recording. Typing a fake sk-xxxxx produces a misleading artifact; recapture with the real credential set out of frame instead. Two specific failures:

- Re-exporting a fake value visibly (export API_KEY=REDACTED) overwrites the real env var, so the demo breaks (401, Unauthorized, 0 credits remaining, empty output). You leak the variable name *and* ship a broken product. - Planning to blur or crop later. Assume anything shown is leaked; recapture is the only remediation.

  • Scan before upload. Look for sk-, ghp_, ghs_, xoxb-, Bearer, Authorization:, ?token=, api_key=, long hex/base64 near credential-sounding labels, or visible .env contents. If any appear, discard and recapture. Never blur or crop.

Arguments

Parse $ARGUMENTS:

  • What to capture: A description of the feature or behavior to demonstrate. If provided, use it to guide which pages to visit, commands to run, or states to capture.
  • If blank, infer what to capture from recoverable branch or PR context. If the target remains ambiguous after that, ask the user what they want to demonstrate before proceeding.

Step 0: Discover Capture Target

Treat target discovery as stateless and branch-aware. The agent may be invoked in a fresh session after the work was already done, so do not rely on conversation history or assume the caller knows the right artifact.

If invoked by another skill, treat the caller-provided target as a hint, not proof. Rerun target discovery and validation before capturing anything.

Use the lightest available context to identify the best evidence target:

  • Current branch name
  • Open PR title and description, if one exists
  • Changed files and diff against the base branch
  • Recent commits
  • A plan file only when it is obviously referenced by the branch, PR, arguments, or caller context

Form a capture hypothesis: "The best evidence appears to be [behavior]."

Proceed without asking only when there is exactly one high-confidence observable behavior and a plausible way to exercise it from the workspace. Ask the user what to demonstrate when multiple behaviors are plausible, the diff does not reveal how to exercise the behavior, or the requested target cannot be mapped to a product surface.

Skip evidence with a clear reason when the diff is docs-only, markdown-only, config-only, CI-only, test-only, or a pure internal refactor with no observable output change.

Step 1: Exercise the Feature

Before capturing anything, verify the feature works by actually using it:

  • CLI tool: Run the new/changed command and confirm the output is correct
  • Web app: Navigate to the new/changed page and confirm it renders correctly
  • Library: Run example code using the new/changed API
  • Bug fix: Reproduce the original bug scenario and confirm it's fixed

Use the workspace where the feature was built. Do not reinstall from scratch. If setup requires credentials or services, use the platform's blocking question tool: AskUserQuestion in Claude Code (call ToolSearch with select:AskUserQuestion first if its schema isn't loaded), request_user_input in Codex, ask_user in Gemini, ask_user in Pi (requires the pi-ask-user extension). Fall back to asking in chat only when no blocking tool exists in the harness or the call errors (e.g., Codex edit modes) — not because a schema load is required. Never silently skip the question.

Step 2: Detect Project Type

Use the capture target from Step 0 to decide which directory to classify. If the diff touches a specific subdirectory with its own package manifest (e.g., packages/cli/, apps/web/), pass that as the root. Otherwise use the repo root.

python3 scripts/capture-demo.py detect --repo-root [TARGET_DIR]

This outputs JSON with type and reason. The result is a signal, not a gate. If the agent's understanding from Step 0 contradicts the script's classification (e.g., the diff clearly changes CLI behavior but the repo root classifies as web-app because of a sibling Next.js app), the agent's judgment wins.

Step 3: Assess Change Type

Step 0 already handled the "no observable behavior" early exit. This step classifies changes that DO have observable behavior into motion or states to guide tier selection.

If arguments describe what to capture, classify based on the description. Otherwise, use the diff context from Step 0.

Change classification:

  1. Involves motion or interaction? (animations, typing flows, drag-and-drop, real-time updates, continuous CLI output) -> classify as motion.
  2. Involves discrete states? (before/after UI, new page, command with output, API response) -> classify as states.
Change characteristicClassification
Animations, typing, drag-and-drop, streaming outputmotion
New UI, before/after, command output, API responsesstates

Feature vs bug fix -- what to demonstrate:

  • New feature (feat): Demonstrate the feature working. Show the hero moment -- the feature doing its thing.
  • Bug fix (fix): Show before AND after. Reproduce the original broken state (if possible) then show the fix. If the broken state can't be reproduced (already fixed in the workspace), capture the fixed state and describe what was broken.

Infer feat vs fix from commit messages, branch name, or plan file frontmatter (type: feat or type: fix). If unclear, ask.

Step 4: Tool Preflight

Run the preflight check:

python3 scripts/capture-demo.py preflight

This outputs JSON with boolean availability for each tool: agent_browser, vhs, silicon, ffmpeg, ffprobe. Print a human-readable summary for the user based on the result, noting install commands for missing tools (e.g., brew install charmbracelet/tap/vhs for vhs, brew install silicon for silicon, brew install ffmpeg for ffmpeg).

Step 5: Create Run Directory

Create a per-run scratch directory in the OS temp location:

mktemp -d -t demo-reel-XXXXXX

Use the output as RUN_DIR. Pass this concrete run directory to every tier reference. Evidence artifacts are ephemeral — they get uploaded to a public URL and then discarded. The OS temp directory is the right place for them, not the repo tree.

Step 6: Recommend Tier and Ask User

Run the recommendation script with the project type from Step 2, change classification from Step 3, and preflight JSON from Step 4:

python3 scripts/capture-demo.py recommend --project-type [TYPE] --change-type [motion|states] --tools '[PREFLIGHT_JSON]'

This outputs JSON with recommended (the best tier), available (list of tiers whose tools are present), and reasoning.

Present the available tiers to the user via the platform's blocking question tool: AskUserQuestion in Claude Code (call ToolSearch with select:AskUserQuestion first if its schema isn't loaded), request_user_input in Codex, ask_user in Gemini, ask_user in Pi (requires the pi-ask-user extension). Fall back to numbered options in chat only when no blocking tool exists in the harness or the call errors (e.g., Codex edit modes) — not because a schema load is required. Never silently skip the question. Mark the recommended tier. Always include "No evidence needed" as a final option.

Question: "How should evidence be captured for this change?"

Options (show only tiers from the available list, order by recommendation):

  1. Browser reel -- Agent-browser screenshots stitched into animated GIF. Best for web apps.
  2. Terminal recording -- VHS terminal recording to GIF. Best for CLI tools with interaction/motion.
  3. Screenshot reel -- Styled terminal frames stitched into animated GIF. Best for discrete CLI steps.
  4. Static screenshots -- Individual PNGs. Fallback when other tools are unavailable.
  5. No evidence needed -- The diff speaks for itself. Best for text-only or config changes.

If the question tool is unavailable (background agent, batch mode), present the numbered options and wait for the user's reply before proceeding.

Step 7: Execute Selected Tier

Carry the capture hypothesis from Step 0 and the feature exercise results from Step 1 into tier execution — these determine which specific pages to visit, commands to run, or states to screenshot. Substitute [RUN_DIR] in the tier reference with the concrete path from Step 5.

Load the appropriate reference file for the selected tier:

  • Browser reel -> Read references/tier-browser-reel.md
  • Terminal recording -> Read references/tier-terminal-recording.md
  • Screenshot reel -> Read references/tier-screenshot-reel.md
  • Static screenshots -> Read references/tier-static-screenshots.md
  • No evidence needed -> Skip to output. Set evidence_url to null, evidence_label to null.

Runtime failure fallback: If the selected tier fails during execution (tool crashes, server not accessible, recording produces empty output), fall back to the next available tier rather than failing entirely. The fallback order is: browser reel -> static screenshots, terminal recording -> screenshot reel -> static screenshots, screenshot reel -> static screenshots. Static screenshots is the terminal fallback -- if even that fails, report the failure and let the user decide.

Step 8: Upload and Approval

After the selected tier produces an artifact, read references/upload-and-approval.md for upload to a public host, user approval gate, and markdown embed generation.

Output

Return these values to the caller (e.g., ce-commit-push-pr):

=== Evidence Capture Complete ===
Tier: [browser-reel / terminal-recording / screenshot-reel / static / skipped]
Description: [1 sentence describing what the evidence shows]
URL: [public URL or "none" (multiple URLs comma-separated for static screenshots)]
Path: [local file path or "none" (multiple paths comma-separated for static screenshots)]
=== End Evidence ===

The Description is a 1-line summary derived from the capture hypothesis in Step 0 (e.g., "CLI detect command classifying 3 project types and recommending capture tiers"). The caller decides how to format the URL(s) into the PR description.

  • Tier: skipped means no evidence was captured; both URL and Path are "none".
  • When uploaded to catbox: URL has the public URL, Path is "none".
  • When saved locally: Path has the local file path, URL is "none".
  • For all non-skipped tiers, exactly one of URL or Path contains a real value; the other is "none".

Label convention:

  • Browser reel, terminal recording, screenshot reel: label as "Demo"
  • Static screenshots: label as "Screenshots"
  • The caller applies the label when formatting. ce-demo-reel does not generate markdown.
  • Test output is never labeled "Demo" or "Screenshots"

平台分布

Codex

34.65%
按下载量换算370

Claude

33.12%
按下载量换算353

Cursor

16.98%
按下载量换算181

Gemini CLI

9.08%
按下载量换算97

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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