ce-demo-reel 是做什么的？
为 PR 描述捕获一个视觉演示卷轴（GIF、终端录制、截图）。适用于交付 UI 变更、CLI 功能或任何具有可观察行为、需要视觉证明的工作。当被要求添加演示、录制 GIF、截图功能、展示视觉变更、创建演示卷轴、捕获证据、为 PR 添加证明或创建前后对比时，同样可以使用该技能。
为 PR 描述捕获视觉演示卷轴（GIF、终端录制、截图）。适用于交付 UI 变更、CLI 功能或任何具有可观察行为、需要视觉证明的工作。
该技能用于自动生成 PR 的视觉演示材料，包括 GIF 动图、终端录制和截图。它特别适合在提交 UI 变更、CLI 新功能或任何具有可视化效果的工作时使用，能够为代码审查提供直观的“证据”。技能支持多种触发方式，例如当被要求“添加演示”、“录制 GIF”、“截图功能”、“展示视觉变更”或“创建前后对比”时，它会主动捕获相关视觉内容。此外，该技能能智能识别需要视觉证明的场景，并自动生成演示卷轴，从而减少人工录制和截图的工作量，提升 PR 描述的质量和可信度。
npx skills add https://github.com/everyinc/compound-engineering-plugin/tree/main/skills/ce-demo-reelInstalled? Explore more 图像 skills: steipete/songsee, affaan-m/frontend-design, mattpocock/improve-codebase-architecture · View all 6 →
为 PR 描述捕获一个视觉演示卷轴（GIF、终端录制、截图）。适用于交付 UI 变更、CLI 功能或任何具有可观察行为、需要视觉证明的工作。当被要求添加演示、录制 GIF、截图功能、展示视觉变更、创建演示卷轴、捕获证据、为 PR 添加证明或创建前后对比时，同样可以使用该技能。
This repo contains 20 individual skills — each has its own dedicated page.
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
Run comprehensive agent-native architecture review with scored principles
Explore requirements and approaches through collaborative dialogue, then write a right-sized requirements document. Use when the user says "let's brainstorm", "what should we build", or "help me think through X", presents a vague or ambitious feature request, or seems unsure about scope or direction -- even without explicitly asking to brainstorm.
Clean up local branches whose remote tracking branch is gone. Use when the user says "clean up branches", "delete gone branches", "prune local branches", "clean gone", or wants to remove stale local branches that no longer exist on the remote. Also handles removing associated worktrees for branches that have them.
Structured code review using tiered persona agents, confidence-gated findings, and a merge/dedup pipeline. In interactive mode it applies safe, verified fixes and commits them when the working tree is clean (it never pushes); in mode:agent it reports only and the caller applies. Use when reviewing code changes before creating a PR.
Create a git commit with a clear, value-communicating message. Use when the user says "commit", "commit this", "save my changes", "create a commit", or wants to commit staged or unstaged work. Produces well-structured commit messages that follow repo conventions when they exist, and defaults to conventional commit format otherwise.
Commit, push, and open a PR with an adaptive, value-first description that scales in depth with the change. Use when the user says "commit and PR", "ship this", "create a PR", or "open a pull request". Also handles description-only flows ("write a PR description", "rewrite the PR body", "describe this PR") without committing or pushing.
Document a recently solved problem to compound your team's knowledge or CONCEPTS.md, the project's shared domain vocabulary.
Refresh stale learning and pattern docs under docs/solutions/ by reviewing them against the current codebase, then updating, consolidating, or deleting drifted ones. Use when the user asks to "refresh my learnings", "audit docs/solutions/", "clean up stale learnings", or "consolidate overlapping docs", or when ce-compound flags an older doc as superseded. Do not trigger for general refactor, debugging, or code-review work unless the user has explicitly pointed at docs/solutions/.
Systematically find root causes and fix bugs. Use when debugging errors, investigating test failures, reproducing bugs from issue trackers (GitHub, Linear, Jira), or when stuck on a problem after failed fix attempts. Also use when the user says 'debug this', 'why is this failing', 'fix this bug', 'trace this error', or pastes stack traces, error messages, or issue references.
This skill should be used when writing Ruby and Rails code in DHH's distinctive 37signals style. It applies when writing Ruby code, Rails applications, creating models, controllers, or any Ruby file. Triggers on Ruby/Rails code generation, refactoring requests, code review, or when the user mentions DHH, 37signals, Basecamp, HEY, or Campfire style. Embodies REST purity, fat models, thin controllers, Current attributes, Hotwire patterns, and the "clarity over cleverness" philosophy.
Review requirements or plan documents using parallel persona agents that surface role-specific issues. Use when a requirements document or plan document exists and the user wants to improve it.
Build web interfaces with genuine design quality, not AI slop. Use for any frontend work - landing pages, web apps, dashboards, admin panels, components, interactive experiences. Activates for both greenfield builds and modifications to existing applications. Detects existing design systems and respects them. Covers composition, typography, color, motion, and copy. Verifies results via screenshots before declaring done.
This skill should be used when generating and editing images using the Gemini API (Nano Banana Pro). It applies when creating images from text prompts, editing existing images, applying style transfers, generating logos with text, creating stickers, product mockups, or any image generation/manipulation task. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images.
Generate and critically evaluate grounded ideas about a topic. Use when asking what to improve, requesting idea generation, exploring surprising directions, or wanting the AI to proactively suggest strong options before brainstorming one in depth. Triggers on phrases like 'what should I improve', 'give me ideas', 'ideate on X', 'surprise me', 'what would you change', or any request for AI-generated suggestions rather than refining the user's own idea.
Run metric-driven iterative optimization loops -- define a measurable goal, run parallel experiments, measure each against hard gates or LLM-as-judge scores, keep improvements, and converge on the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation.
Create structured plans for multi-step tasks -- software features, research workflows, events, study plans, or any goal that benefits from breakdown. Also deepens existing plans with interactive sub-agent review. Use when the user says 'plan this', 'create a plan', 'how should we build', 'break this down', or when a brainstorm doc is ready for planning. Use 'deepen the plan' or 'deepening pass' for the deepening flow. For exploratory requests, prefer ce-brainstorm first.
[BETA] Start the dev server, open the feature in a browser, and iterate on improvements together.
Generate a time-windowed pulse report on what users experienced and how the product performed - usage, quality, errors, signals worth investigating. Use when the user says 'run a pulse', 'show me the pulse', 'how are we doing', 'weekly recap', 'launch-day check', or passes a time window like '24h' or '7d'. Configures via .compound-engineering/config.local.yaml and saves reports to docs/pulse-reports/.
Publish, view, comment on, and edit markdown via Proof (proofeditor.ai) — create a shareable doc, read a shared doc, and make comment/suggestion/block edits over its API. Use when the user says "view this in proof", "share to proof", "publish to proof", or wants a shareable markdown surface for a spec, plan, or draft, including publish handoffs from ce-brainstorm, ce-ideate, or ce-plan. Do not trigger on "proof" meaning evidence, math proofs, proof-of-concept, or "proofread this".
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Add documentation for a new AI provider — usage docs, env vars, Docker config, image resources.
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.