Step 1 of 6
Inspect Existing Data Model and API
Identify where the target data lives and how it is currently fetched.
The app is already running; its data is exposed via a REST endpoint GET /items returning JSON array of objects with id, name, description fields.
1. Open the main repository and locate the file that defines the item data model (e.g., Item.js, schema.sql, or a TypeScript interface). 2. List all fields, their types, and any indexes. 3. Find the client‑side code that retrieves the list (e.g., a fetch call or Axios request). 4. Copy the full URL, request method, headers, and response handling logic. 5. Ensure the snippet includes error handling and state update. 6. Provide a short comment explaining how the data currently populates the UI list.
Expected after this step
A code block showing the exact data model definition and the real fetch implementation used by the app.
Should not happen
- ✕AI returns commented‑out or placeholder code instead of real implementations.
- ✕Mocked API responses are used rather than actual DB queries.
- ✕SearchBar UI contains dummy text or lacks real Tailwind classes.
- ✕Persistence step uses in‑memory variables instead of localStorage.
Verify before continuing
Do not move on until every check is true. The complete button stays locked until then.
Do not continue if…
- !AI returns commented‑out or placeholder code instead of real implementations.
- !Mocked API responses are used rather than actual DB queries.
- !SearchBar UI contains dummy text or lacks real Tailwind classes.
- !Persistence step uses in‑memory variables instead of localStorage.
- !Documentation or commit steps are omitted.
- !Self‑audit PASS/FAIL statements are missing or always claim PASS without verification.
If the AI messes this up
Use this when the AI fakes progress or breaks the feature. It forces a real fix.
The AI presented fabricated file names or placeholder URLs. Re‑run the prompt and require the exact existing file paths and real request code without any invented elements.