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Preventing Feature Skipping in Lovable Code Generation

Lovable skips features from your prompt when the request is too broad, requirements are buried in long paragraphs, or the AI prioritizes some features over others. Prevent skipping by using numbered lists for every requirement, building one feature at a time with verification between each, using Plan Mode to confirm all items are in the implementation plan, and asking the AI to confirm which items it completed after each generation.

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Intermediate9 min read~10 min per featureAll Lovable projectsMarch 2026RapidDev Engineering Team
TL;DR

Lovable skips features from your prompt when the request is too broad, requirements are buried in long paragraphs, or the AI prioritizes some features over others. Prevent skipping by using numbered lists for every requirement, building one feature at a time with verification between each, using Plan Mode to confirm all items are in the implementation plan, and asking the AI to confirm which items it completed after each generation.

Why Lovable ignores details without clear prompt structure

Large language models process text sequentially and have limited attention for long, unstructured prompts. When you send a prompt with 10 requirements described in paragraph form, the AI focuses on the most prominent ones and may silently skip others, especially those mentioned briefly at the end. This is different from the 'ensuring all features' page because it focuses specifically on preventing the AI from skipping items — the mechanics of why features get dropped and the specific techniques to ensure every single requirement is addressed. The key insight is that numbered lists, explicit completion tracking, and post-generation verification form a closed loop that catches omissions. Lovable's AI performs best with clear, structured input. A numbered list of 5 items is much harder to skip than 5 sentences in a paragraph. And asking the AI to confirm which items it completed creates accountability that reduces the chance of silent omissions.

  • Requirements written as prose paragraphs instead of numbered lists
  • Too many features requested in a single prompt, exceeding the AI's reliable processing capacity
  • Critical details mentioned briefly at the end of a long prompt where AI attention is lowest
  • No post-generation verification step to catch skipped items
  • Dependencies between features are not made explicit, so the AI skips dependent features

Error messages you might see

Feature not implemented despite being in the prompt

The AI silently dropped a requirement. This produces no error message — the code works but is incomplete. Always verify each numbered item against the generated output.

Partial implementation of a feature

The AI implemented the basic version but skipped edge cases or secondary behaviors. For example, it added a table but skipped pagination. Send a follow-up prompt for the missing pieces.

Wrong interpretation led to a different feature being built

The AI misunderstood a requirement and built something different. This is worse than skipping because it consumes credits on the wrong feature. Use Plan Mode to verify interpretation.

Before you start

  • A Lovable project where you need multiple features implemented completely
  • A written list of all requirements before starting
  • Familiarity with Plan Mode and @file references

How to fix it

1

Convert all requirements to a numbered list

Numbered lists create discrete, trackable items that are harder for the AI to silently skip

Before sending any prompt, write every requirement as a numbered item. Be specific enough that you can verify each item by looking at the preview. A vague item like '3. Good UI' cannot be verified. A specific item like '3. Table with columns: Name, Email, Role, and a blue header row' can be checked in seconds.

Before
typescript
// Prose prompt (easy to skip items):
// "Build a settings page with a profile section where users can
// update their name and email, a notification preferences section
// with toggle switches, a password change form, and a delete account
// button with a confirmation dialog."
After
typescript
// Numbered list (hard to skip):
// Build a settings page with these features:
// 1. Profile section with name and email text inputs
// 2. A Save button that updates the profile in Supabase
// 3. Notification preferences section with 3 toggle switches:
// Email notifications, Push notifications, SMS notifications
// 4. Password change form with: current password, new password,
// confirm password fields and a Change Password button
// 5. Delete Account button (red, at the bottom) that shows a
// confirmation dialog before deleting

Expected result: Each numbered item is a discrete, verifiable feature. You can check each one against the preview.

2

Ask the AI to confirm completion of each item

Explicit confirmation creates a feedback loop that catches omissions before you close the chat

At the end of your prompt, add: 'After implementation, list which numbered items you completed and which you could not. If you skipped any, explain why.' This forces the AI to review its own output against your requirements. If it reports skipping an item, you can immediately send a follow-up prompt for that specific feature.

Before
typescript
// No completion tracking:
// "Build these 5 features" → AI responds with code
// You assume everything is done but item 4 is missing
After
typescript
// With completion tracking:
// "Build these 5 features. After implementation, confirm which
// items you completed:
// 1. Profile section with name/email inputs ✓/✗
// 2. Save button connected to Supabase ✓/✗
// 3. Notification toggles (3 switches) ✓/✗
// 4. Password change form ✓/✗
// 5. Delete account with confirmation dialog ✓/✗"
//
// AI response: "Completed items 1, 2, 3, 5.
// Item 4 was not implemented because [reason]."

Expected result: You know exactly which items were completed and which need follow-up prompts.

3

Build one feature at a time for critical requirements

Single-feature prompts have the highest completion rate because the AI focuses entirely on one task

For features that absolutely must work correctly (payments, authentication, data operations), send one feature per prompt. Wait for the generation to complete, verify it in the preview, and only then move to the next feature. This approach uses more prompts but guarantees each feature is fully implemented. Use @file references to direct each prompt to the correct file.

Before
typescript
// All features in one prompt:
// "Build the entire settings page with 5 features"
After
typescript
// One feature per prompt:
// Prompt 1: "Create @src/pages/Settings.tsx with a profile
// section showing name and email inputs"
// → Verify in preview ✓
//
// Prompt 2: "Add a Save button to @src/pages/Settings.tsx
// that updates the profile in Supabase"
// → Verify by clicking Save ✓
//
// Prompt 3: "Add notification preference toggles to
// @src/pages/Settings.tsx: Email, Push, and SMS"
// → Verify by toggling each switch ✓

Expected result: Each feature is fully implemented and verified before moving to the next one.

4

Use Plan Mode to verify the implementation plan includes all items

Plan Mode shows what the AI intends to build, letting you catch omissions before code is generated

For complex features with many requirements, switch to Plan Mode first. Send your numbered list and ask for a detailed implementation plan. Review the plan to ensure every numbered item is addressed. If any item is missing, add it before switching to Agent Mode. If using Plan Mode and incremental prompting across many features gets complex, RapidDev's engineers have managed this workflow across 600+ Lovable projects.

Before
typescript
// Skipping Plan Mode → hoping everything is included
After
typescript
// Plan Mode first:
// "Plan the implementation of these 5 features.
// For each numbered item, describe which file you will
// modify and what the implementation will look like.
// Do not write code yet."
//
// Review plan → all 5 items listed → "Implement the plan"

Expected result: The plan confirms all requirements are included. Implementation follows the verified plan exactly.

Complete code example

AGENTS.md
1# Feature Implementation Rules
2
3## Prompt Processing
4- Treat every numbered item as a required feature
5- Do NOT skip any numbered item
6- If an item cannot be implemented, explain why in your response
7- After implementation, list completion status of each item
8
9## Implementation Order
101. Read all numbered requirements first
112. Plan the implementation of ALL items before coding
123. Implement items in the order listed
134. After each item, verify it works before moving to the next
145. Report completion status at the end
15
16## When Requirements Are Unclear
17- Ask for clarification instead of guessing
18- Do not interpret 'etc.' or 'and so on' ask for the specific items
19- If a requirement conflicts with another, flag it
20
21## Quality Checks
22- Every button must have a working onClick handler
23- Every form must have proper validation
24- Every table must handle the empty state
25- Every list must handle pagination if more than 20 items
26
27## Response Format
28After implementing features, respond with:
29- Completed: [list of completed item numbers]
30- Skipped: [list of skipped item numbers with reasons]
31- Modified files: [list of files changed]

Best practices to prevent this

  • Always use numbered lists for requirements — never prose paragraphs
  • Put the most critical features first in the list — AI attention is highest at the beginning
  • Add 'Confirm completion of each numbered item' to the end of every multi-feature prompt
  • Build one feature at a time for critical requirements like payments and authentication
  • Use Plan Mode for any prompt with more than 3 requirements to verify the plan before building
  • Verify each feature in the preview immediately after generation, before sending the next prompt
  • If a feature is skipped, send a dedicated follow-up prompt for just that feature with @file reference
  • Add feature implementation rules to AGENTS.md to make the AI report completion status automatically

Still stuck?

Copy one of these prompts to get a personalized, step-by-step explanation.

ChatGPT Prompt

I gave Lovable a prompt with 5 numbered requirements, but it only implemented 3 of them. Here is my original prompt: [paste your prompt] And here is what was actually built: [describe what you see in the preview] Please: 1. Identify which requirements were skipped 2. Write a specific follow-up prompt for each skipped requirement 3. Suggest how to restructure my original prompt to prevent skipping 4. Write AGENTS.md rules for feature completion tracking

Lovable Prompt

You skipped items 3 and 5 from my previous prompt. Please implement them now: 3. Add notification preference toggles to @src/pages/Settings.tsx: three toggle switches for Email notifications, Push notifications, and SMS notifications. Each toggle should save its state to Supabase. 5. Add a Delete Account button at the bottom of @src/pages/Settings.tsx. The button should be red (destructive variant). When clicked, show a confirmation dialog that says 'This action cannot be undone.' Only delete the account if the user confirms. After implementation, confirm: Item 3 ✓/✗, Item 5 ✓/✗

Frequently asked questions

Why does Lovable skip features from my prompt?

AI models have limited attention for long prompts. Features at the end of paragraphs or described briefly are most likely to be dropped. Use numbered lists and keep prompts focused on 3-5 items maximum.

How do I make sure every feature is implemented?

Use three techniques together: numbered requirements, Plan Mode verification before building, and asking the AI to confirm completion of each item after building. For critical features, build one per prompt.

What is the difference between this page and the ensuring-all-features page?

This page focuses specifically on the mechanics of preventing the AI from skipping items: numbered lists, completion tracking, and single-feature prompts. The ensuring-all-features page covers the broader strategy including Plan Mode workflows and incremental building.

How many features can I reliably include in one prompt?

3-5 numbered items is the reliable sweet spot. For simple features, you can include up to 5. For complex features, 1-2 per prompt is safer. Beyond 5, the skip rate increases significantly.

Can I prevent skipping with AGENTS.md rules?

Partially. Add rules like 'Implement every numbered item' and 'Report completion status for each item.' This improves compliance but does not guarantee 100% completion for very complex prompts.

What if I can't fix this myself?

If your project has many incomplete features and tracking them across prompts is overwhelming, RapidDev's engineers can systematically implement every missing feature. They have completed feature backlogs across 600+ Lovable projects.

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