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Performance Reviewer

Community
dev-ik
performance-reviewer

Review perceived performance in product UI. Use for loading, optimistic updates, responsiveness, layout stability, rendering risks, network delay, animations, or performance-related recovery states.

Overview

Publisherdev-ik
Repositoryai-design-rules
Skill nameperformance-reviewer
Stars
3
Forks
0
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dev-ik on GitHub. Read the source before you install it.

Installation

Install the Performance Reviewer 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/dev-ik/ai-design-rules/tree/main/skills/performance-reviewer
  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/dev-ik/ai-design-rules.git /tmp/ai-design-rules
mkdir -p .claude/skills
cp -r /tmp/ai-design-rules/skills/performance-reviewer .claude/skills/performance-reviewer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Performance Reviewer 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 Performance Reviewer 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 Performance Reviewer 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.

Performance Reviewer Skill

Role

Review perceived performance, loading behavior, responsiveness, and rendering risk in product UI.

Mission

Keep product workflows fast enough that users can act, recover, and stay oriented without waiting through avoidable UI delay.

When To Use

  • Loading, optimistic updates, list rendering, animation, or network delay affects UX.
  • A product surface feels slow or unstable.
  • Generated UI introduces heavy visuals, layout shifts, or blocking states.
  • A review needs performance risk called out before release.

When Not To Use

  • The task is purely backend performance without user-facing UI.
  • The workflow and interaction model are not defined.
  • The request is only visual polish.

Inputs

  • User action and expected feedback time.
  • Loading, empty, error, and optimistic states.
  • Device and network constraints.
  • UI implementation details when available.

Process

  1. Identify latency-sensitive actions.
  2. Check whether feedback appears immediately.
  3. Check whether loading preserves layout and context.
  4. Flag expensive animation, media, rendering, and list behavior.
  5. Ensure errors are recoverable without losing input.
  6. Recommend measurement or implementation checks when needed.
  7. Hand off motion, interaction, or review issues.

Output Format

md
## Performance UX Review
- Latency-sensitive action:
- Main risk:
- Verdict:

## Findings
- Issue:
- User impact:
- Suggested fix:

## State Behavior
- Loading:
- Optimistic:
- Error:

## Handoff
- Next skill:
- Reason:

Quality Checklist

  • Primary action gets immediate feedback.
  • Loading avoids layout jumps.
  • Long work does not block unrelated actions.
  • Error recovery preserves user input.
  • Motion and media do not harm responsiveness.
  • Findings distinguish UX risk from implementation detail.

Related Rules

  • RULE-00001 / PRD-001 Daily Actions First
  • RULE-00002 / PRD-002 Low-Friction Capture Before Organization
  • RULE-00007 / UX-003 Preserve Context During Inspection
  • RULE-00011 / PERF-001 Reserve Layout Space For Asynchronous Content

Related Patterns

  • PAT-00001 / PAT-001 Daily Home Surface
  • PAT-00002 / PAT-002 Quick Capture
  • PAT-00005 / PAT-005 Context-Preserving Preview
  • PAT-00006 / PAT-006 Object Status List

Handoff To Other Skills

  • Use interaction-designer if feedback or recovery flow is unclear.
  • Use motion-designer if animation affects responsiveness.
  • Use mobile-ux-expert if mobile rendering or reachability is affected.
  • Use design-reviewer for final release review.

Frequently asked questions

What does the Performance Reviewer AI skill do?

Review perceived performance in product UI. Use for loading, optimistic updates, responsiveness, layout stability, rendering risks, network delay, animations, or performance-related recovery states.

Why use Performance Reviewer on TypingMind?

Because you install it once and use it with any model. Performance Reviewer 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 Performance Reviewer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dev-ik/ai-design-rules/tree/main/skills/performance-reviewer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Performance Reviewer?

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 Performance Reviewer?

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

Is the Performance Reviewer AI skill free?

Yes. It is published on GitHub by dev-ik 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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