Feedback Form logo

Feedback Form

Community
rshankras
feedback-form

Generates an in-app feedback collection form with category selection, text input, optional screenshot attachment, device diagnostics, and smart routing — directing happy users to App Store reviews and unhappy users to support. Use when user wants feedback, bug reports, feature requests, or contact support forms.

Overview

Publisherrshankras
Repositoryclaude-code-apple-skills
Skill namefeedback-form
Stars
744
Forks
70
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 rshankras on GitHub. Read the source before you install it.

Installation

Install the Feedback Form 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.
  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/rshankras/claude-code-apple-skills.git /tmp/claude-code-apple-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-apple-skills/skills/generators/feedback-form .claude/skills/feedback-form
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feedback Form 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 Feedback Form 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 Feedback Form 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.

Feedback Form Generator

Generate a production in-app feedback form with category selection, sentiment-based rating, optional screenshot attachment, device diagnostics collection, and smart routing that funnels satisfied users to the App Store review prompt and dissatisfied users to a support channel.

When This Skill Activates

Use this skill when the user:

  • Asks to "add a feedback form" or "feedback form"
  • Wants "in-app feedback" or "user feedback" collection
  • Mentions "bug report form" or "feature request" form
  • Asks about "contact support" from within the app
  • Wants "feedback collection" with categories or screenshots
  • Asks to "route users to App Store review" based on sentiment

Pre-Generation Checks

1. Project Context Detection

  • Check Swift version (requires Swift 5.9+)
  • Check deployment target (iOS 16+ / macOS 13+)
  • Check for @Observable support (iOS 17+ / macOS 14+)
  • Identify source file locations

2. Conflict Detection

Search for existing feedback or support code:

Glob: **/*Feedback*.swift, **/*Support*.swift, **/*BugReport*.swift, **/*ContactForm*.swift
Grep: "MFMailComposeViewController" or "FeedbackForm" or "SKStoreReviewController"

If third-party feedback SDK found (Instabug, UserVoice, Zendesk):

  • Ask if user wants to replace or keep it
  • If keeping, don't generate — advise on best practices instead

3. Framework Detection

Check for MessageUI availability:

Grep: "import MessageUI" or "MFMailCompose"

Note: MessageUI is iOS-only. macOS uses NSSharingService or direct webhook delivery.

Configuration Questions

Ask user via AskUserQuestion:

  1. Feedback categories? (multi-select)

    • Bug Report
    • Feature Request
    • General Feedback
    • Praise
    • Other
    • All of the above — recommended
  2. Delivery method?

    • Email (via MFMailComposeViewController / NSSharingService)
    • Webhook (POST to a URL endpoint)
    • Both — recommended
  3. Include screenshot capture?

    • Yes — recommended (capture current screen + annotation overlay)
    • No
  4. Include device diagnostics?

    • Yes — recommended (device model, OS, app version, disk, memory)
    • No
  5. Sentiment routing?

    • Yes — recommended (rating >= 4 suggests App Store review, rating <= 2 routes to support)
    • No (all feedback goes through the same channel)

Generation Process

Step 1: Read Templates

Read templates.md for production Swift code.

Step 2: Create Core Files

Generate these files:

  1. FeedbackCategory.swift — Enum with SF Symbol icons and display names
  2. FeedbackEntry.swift — Data model for a feedback submission
  3. DeviceDiagnostics.swift — Collects device and app info

Step 3: Create UI Files

  1. FeedbackFormView.swift — SwiftUI form with sentiment, category, message, screenshots

Step 4: Create Delivery Files

  1. FeedbackSubmitter.swift — Protocol + EmailFeedbackSubmitter + WebhookFeedbackSubmitter

Step 5: Create Optional Files

Based on configuration:

  • ScreenshotCapture.swift — If screenshot capture selected

Step 6: Determine File Location

Check project structure:

  • If Sources/ exists -> Sources/Feedback/
  • If App/ exists -> App/Feedback/
  • Otherwise -> Feedback/

Output Format

After generation, provide:

Files Created

Feedback/
├── FeedbackCategory.swift       # Category enum with icons
├── FeedbackEntry.swift          # Feedback data model
├── DeviceDiagnostics.swift      # Device info collector
├── FeedbackFormView.swift       # SwiftUI form view
├── FeedbackSubmitter.swift      # Email + webhook delivery
└── ScreenshotCapture.swift      # Screen capture (optional)

Integration Steps

Present the feedback form from any view:

swift
@State private var showFeedback = false

Button("Send Feedback") {
    showFeedback = true
}
.sheet(isPresented: $showFeedback) {
    FeedbackFormView()
}

In a settings screen:

swift
Form {
    Section("Support") {
        Button {
            showFeedback = true
        } label: {
            Label("Send Feedback", systemImage: "bubble.left.and.text.bubble.right")
        }
    }
}
.sheet(isPresented: $showFeedback) {
    FeedbackFormView()
}

With a pre-selected category (e.g., from a help menu):

swift
FeedbackFormView(initialCategory: .bugReport)

Testing

swift
@Test
func feedbackEntryEncodesCorrectly() throws {
    let entry = FeedbackEntry(
        category: .bugReport,
        message: "App crashes when tapping save",
        rating: 2,
        screenshots: [],
        deviceInfo: DeviceDiagnostics.collect(),
        appVersion: "1.2.3",
        timestamp: Date()
    )

    let data = try JSONEncoder().encode(entry)
    let decoded = try JSONDecoder().decode(FeedbackEntry.self, from: data)
    #expect(decoded.category == .bugReport)
    #expect(decoded.rating == 2)
}

@Test
func webhookSubmitterSendsCorrectPayload() async throws {
    let mockSession = MockURLSession()
    let submitter = WebhookFeedbackSubmitter(
        url: URL(string: "https://example.com/feedback")!,
        session: mockSession
    )

    let entry = FeedbackEntry(
        category: .featureRequest,
        message: "Dark mode support please",
        rating: 4,
        screenshots: [],
        deviceInfo: DeviceDiagnostics.collect(),
        appVersion: "1.0.0",
        timestamp: Date()
    )

    try await submitter.submit(entry)
    #expect(mockSession.lastRequest?.httpMethod == "POST")
    #expect(mockSession.lastRequest?.value(forHTTPHeaderField: "Content-Type") == "application/json")
}

@Test
func sentimentRoutingDirectsHighRatingToReview() {
    let entry = FeedbackEntry(
        category: .praise,
        message: "Love this app!",
        rating: 5,
        screenshots: [],
        deviceInfo: DeviceDiagnostics.collect(),
        appVersion: "1.0.0",
        timestamp: Date()
    )

    #expect(entry.suggestsAppStoreReview) // rating >= 4
}

Common Patterns

Open feedback form from a menu bar app

swift
Button {
    showFeedback = true
    NSApp.activate(ignoringOtherApps: true)
} label: {
    Label("Send Feedback", systemImage: "envelope")
}
.sheet(isPresented: $showFeedback) {
    FeedbackFormView()
}

Submit feedback with a screenshot attachment

swift
let screenshot = try await ScreenshotCapture.captureCurrentWindow()
let entry = FeedbackEntry(
    category: .bugReport,
    message: "Layout is broken on this screen",
    rating: 1,
    screenshots: [screenshot],
    deviceInfo: DeviceDiagnostics.collect(),
    appVersion: Bundle.main.appVersion,
    timestamp: Date()
)
try await submitter.submit(entry)

Route by sentiment after submission

swift
if entry.suggestsAppStoreReview {
    // Happy user — ask for App Store review
    if let scene = UIApplication.shared.connectedScenes.first as? UIWindowScene {
        SKStoreReviewController.requestReview(in: scene)
    }
} else if entry.suggestsSupportFollowUp {
    // Unhappy user — show support confirmation
    showSupportConfirmation = true
}

Gotchas

  • MFMailComposeViewController requires a mail account: Check MFMailComposeViewController.canSendMail() before presenting. Fall back to webhook or mailto: URL if unavailable.
  • Screenshot privacy: Consider blurring or redacting sensitive data (passwords, financial info) before attaching. Use UITextField.isSecureTextEntry areas as a guide.
  • Attachment size limits for email: Email attachments are typically limited to 10-25 MB. Compress screenshots to JPEG and resize if needed. Webhook delivery is more reliable for large attachments.
  • Offline submission queuing: If the device is offline when feedback is submitted, queue the entry to disk and retry when connectivity is restored. Use NWPathMonitor to detect network changes.
  • App Store review prompt limits: SKStoreReviewController.requestReview() is rate-limited by the system (typically 3 times per 365-day period). Don't rely on it always appearing.
  • macOS has no MFMailComposeViewController: Use NSSharingService(named: .composeEmail) or prefer webhook delivery on macOS.

References

  • templates.md — All production Swift templates
  • Related: generators/review-prompt — App Store review prompt timing and strategy

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 Feedback Form AI skill do?

Generates an in-app feedback collection form with category selection, text input, optional screenshot attachment, device diagnostics, and smart routing — directing happy users to App Store reviews and unhappy users to support. Use when user wants feedback, bug reports, feature requests, or contact support forms.

Why use Feedback Form on TypingMind?

Because you install it once and use it with any model. Feedback Form 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 Feedback Form in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rshankras/claude-code-apple-skills/tree/main/skills/generators/feedback-form. 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 Feedback Form?

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 Feedback Form?

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

Is the Feedback Form AI skill free?

Yes. It is published on GitHub by rshankras 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇