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Design Review

OrganizationPopular
Prismer-AI
design-review

Five-dimension design audit (frontend UI/UX · server data-model & flow · endpoint spec · daemon-runtime/SDK & local-cache-first · built-in skill/agent-role), executed by a NON-implementing agent. Every dimension gets a verdict; N/A only with a stated reason. A dimension the design silently skipped must be surfaced as a gap; covered dimensions must not be over-reported.

Overview

PublisherPrismer-AI
RepositoryPrismerCloud
Skill namedesign-review
Stars
1.6K
Forks
17
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Prismer-AI on GitHub. Read the source before you install it.

Installation

Install the Design Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/design-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git /tmp/PrismerCloud
mkdir -p .claude/skills
cp -r /tmp/PrismerCloud/sdk/apc/skills/design-review .claude/skills/design-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Design Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Design Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

design-review

对一个改动方案 / diff做 CLAUDE.md 强制的五维变更审计,产出每一维的判定(covered / gap / N-A-带理由),由非实施 agent 执行(apc/05 §2 S6 · apc/12 design-review 行;与 S5 code-review 同精神——实施者不自审自的设计)。

什么时候用:一个 design doc / migration / ADD COLUMN / 新 endpoint / UI 重做进评审门时,需要独立核对它有没有把五维都想全。这是设计期的漏,比 phase 末期补漏便宜 10×(CLAUDE.md 五维审计)。

评审独立性(第一铁律,P2-17)

评审由非实施 agent 执行——设计者不自审自的方案,与 no-self-approval 同精神。若你就是这份设计的作者 → 停手,让另一个 agent 审。

五维(缺一维 = 未闭合;N/A 也要显式写理由)

照 CLAUDE.md「Five-Dimension Change Audit」逐维答。任一维标"未考虑"/"待后续评估"不能进实施;N/A 也要显式写原因。

#维度必答问题(摘 CLAUDE.md)证据手段
1前端 UI/UX 渲染交互用户在哪儿感知?哪些组件/hook/路径改?破坏交互肌肉记忆吗?刷新/跨设备?错误态如何 surface?rg 组件/路由
2服务端 data-model & 数据流哪些 Prisma model / SQL table 改?migration 编号?读/写/缓存路径?同事务保证?跨实例 fan-out?rg schema;ls src/im/sql | sort | tail 看下一个编号;双 Prisma(SQLite + MySQL)都改了吗
3Endpoint spec新增/改/弃用哪些 HTTP/WS/SSE?req/resp schema?认证级别?错误码?兼容策略?SDK 类型同步?rg 路由/handler
4Daemon runtime / SDK & local-cache-firstdaemon SDK 要适配吗?本地 SQLite/FS/asset-cache 变化?离线 fallback?daemon↔cloud 版本协商?多语言 SDK 同步?rg runtime/;想 local-first:cloud-only 的东西 daemon 学得到吗
5Built-in skill / agent-role影响 SKILL.md / AGENTS.md / SOUL.md / operatingPrinciples 吗?要新 built-in skill?role template backfill?agent 端 prompt 更新?rg built-in-skills/ · role template

Procedure

1. 独立性自证(若挂 task)— 你不是设计作者

2. 逐维审,每维产一条判定

对每一维给一行判定,形状:

{ dimension: 1..5,
  verdict: covered | gap | n/a,
  reason: "<covered: 方案怎么覆盖的 + 残留问题 / gap: 漏了什么、会怎么坏 / n/a: 为什么这维不适用>" }
  • gap 是承重判据:方案没提的维度,标 gap 并说清"这个洞会怎么坏"(如:cloud-only 的 cap,daemon 本地 LLM 路径学不到 → 离线不 enforce)。别因为方案没写就默默跳过当它 covered——静默跳过正是五维审计要抓的头号反 pattern(单维过度聚焦)。
  • n/a 必须带理由:一维确实不适用(纯计费门不碰 agent 能力 → 第 5 维 N/A),显式写理由。不许留空、不许"待评估"。
  • covered 不虚报:方案真覆盖的维度,标 covered、只列真实残留问题(错误码待补、跨设备回显待确认)。不要把正常设计说成 blocker——假阳会淹没真信号(照 S5 code-review "干净 diff 不虚报")。

3. 汇总 + 点出被静默跳过的维度

产出:

  • 五维判定表(每维 covered/gap/n-a + reason)。
  • 承重发现:被方案静默跳过的维度(那个 enforcement/兼容/数据主权的洞)。
  • openQuestions[]:拿不准的(不是 gap)。

输出契约(机器判据按这个复验,别自由发挥格式)

本 skill 的验收判据不是「报告里出现了 daemon / prisma 这些词」——旧判据就是六条这样的 match,一句 npm run prisma:generate 就能让"数据模型维已答"变绿。现在判据找的是每一维自己那一行,并把该行的引用读回磁盘复核(structured-criteria.ts 的 dimension-coverage)。

五维逐行作答(每维独占一行 + 固定 key,行首先给 verdict,再给理由,最后给证据):

- [1] frontend-uiux: covered — <覆盖点 + 残留问题> | <path:line>
- [2] server-data-model: covered — <…> | <path:line>
- [3] endpoint-spec: covered — <…> | <path:line>
- [4] daemon-runtime-sdk: gap — <洞是什么、会怎么坏> | <daemon/runtime 侧真要改的 path:line>
- [5] skill-agent-role: gap — <…> | <path:line>    或    N/A — <理由 ≥20 字符>

判据强制三条:

  1. 每维的行必须以 verdict 开头:covered / gap / N/A(中文 已覆盖 / 缺口 / 不适用 同义)。
  2. covered / gap 的行必须带至少一条能在磁盘上复核的 path:line(文件存在、行号在范围内、该行非空)——rg -n 出来的行号,别猜。这就是"对码":说方案漏了 daemon 层,就得指出 daemon 层真正要改的那一行。
  3. N/A 的行必须带理由(去空白后 ≥20 字符);只写 N/A 判红。

引用写法:必须 repo-root-relative(src/im/api/routes.ts:314,不要简写成 im/api/routes.ts:314,也不要绝对路径);rg -c 出的 path:12 是命中计数不是行号,要写就写 count=12。

承重维度的 verdict 是被钉死的:sample task 里 daemon-runtime-sdk 必须是 gap。把它橡皮图章成 covered、或者把 "gap" 写在正文别处而不在那一行上,都判红——这正是五维审计要抓的头号反 pattern(静默跳过)。

产出(副作用 oracle,报告里必须给)

  1. 五维全答:五个维度逐一有判定,无一维留空(N/A 也带理由)。
  2. gap 被 surface:方案静默跳过的维度标成 gap / missing / not-addressed,说清怎么坏——不是橡皮图章全绿。
  3. covered 不虚报:真覆盖的维度不编造 blocker。

不许:把方案没提的维度默默当 covered(静默跳过);一维留空或写"待评估"就交(未闭合);把正常设计说成 blocker 制造假阳;自审自的设计。

诚实边界

  • LLM 设计评审是非确定性的:本 skill 不保证抓出所有设计缺陷,也不保证零漏报/零虚报。它保证的是"五维逐维走一遍 + 每维判定可核验(covered/gap/n-a 带理由)+ gap 说清怎么坏 + 不自审"。深层的跨维耦合缺陷可能漏——靠多轮评审 + 真实施后 test-runner 兜,不靠单次审打包票。
  • 需要读代码核对的维度("这个字段真有消费者吗"/"下一个 migration 编号"),依赖仓库可 rg/ls;只读方案文本时该维标注"未对码,基于方案陈述"。
  • 本 skill 只产判定,不改设计——修由设计者按判定回改,再进下一轮审。

调用回执(APC 平台方运营纪律 · 自动注入,勿手改)

执行本 skill 的第一步,先落一条调用回执:

bash
cloud skill ack design-review --task "$PRISMER_TASK_ID"

按退出码分流(这条命令的退出码是承重信息,禁止用 || 兜底、; true、 set +e 或重定向把它抹掉):

exit含义你要做的
0回执已落库(im_task_logs.action='skill_ack')继续执行本 skill
3无 task 上下文——本次运行没有 task,产不出回执继续执行本 skill;但本次运行没有回执,任何报告里都不得声称已 ack
4你不是该 task 的 assignee,服务端拒绝停下并上报:回执只能由执行该 task 的 agent 产生
1其它失败(网络 / 服务端)重试一次;仍失败则继续执行,并在结果里显式标注「回执缺失」

回执只证明本 skill 被调度,不证明执行正确——效果证明由本 skill 自己的 acceptanceCriteria 副作用断言承担(apc/04 §2 层 1 诚实标注)。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Design Review AI skill do?

Five-dimension design audit (frontend UI/UX · server data-model & flow · endpoint spec · daemon-runtime/SDK & local-cache-first · built-in skill/agent-role), executed by a NON-implementing agent. Every dimension gets a verdict; N/A only with a stated reason. A dimension the design silently skipped must be surfaced as a gap; covered dimensions must not be over-reported.

Why use Design Review on TypingMind?

Because you install it once and use it with any model. Design Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Design Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Prismer-AI/PrismerCloud/tree/main/sdk/apc/skills/design-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Design Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Design Review?

As many as you like. As long as a model supports skills, you can use Design Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Design Review AI skill free?

Yes. It is published on GitHub by Prismer-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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