XXDILI

The available visual captures consistently show only the loading state, so the core live-weather result and search flow could not be visually reviewed. The layout is clean and responsive in the shown initial state, and the completion note names Open-Meteo, but a loaded desktop/mobile capture and a working motion capture would be needed to substantiate the central task.

The available visual captures consistently show only the loading state, so the core live-weather result and search flow could not be visually reviewed. The layout is clean and responsive in the shown initial state, and the completion note names Open-Meteo, but a loaded desktop/mobile capture and a working motion capture would be needed to substantiate the central task.

The available visual captures consistently show only the loading state, so the core live-weather result and search flow could not be visually reviewed. The layout is clean and responsive in the shown initial state, and the completion note names Open-Meteo, but a loaded desktop/mobile capture and a working motion capture would be needed to substantiate the central task.

Nice work adding real wind data, unit toggling, and clear error handling—features a real user would appreciate.

A workable small-server structure with centralized live fetching, but most concerns are still fused into one large server.js. Extracting the weather provider/cache, request routing, and HTML rendering into separate modules would substantially improve architecture and testability.

The implementation correctly fetches real weather from Open-Meteo, isolates data fetching, and avoids duplicating live values, earning a strong score on the data criterion.

Tests verify core behavior but depend on live data values, reducing robustness. Adding more tolerant assertions (e.g., range checks) and unit tests would improve regression safety.

Open-Meteo is clearly named in the completion note and current cards are implemented with shared, readable helpers. Remove or clearly isolate the stale hard-coded forecast path, and make tests assert live-data shape/semantics rather than fixed weather values.

Open-Meteo is clearly named in the completion note and current cards are implemented with shared, readable helpers. Remove or clearly isolate the stale hard-coded forecast path, and make tests assert live-data shape/semantics rather than fixed weather values.

Good completion note and some reusable test/recording automation, but add accurate agent instructions, wire validation into a routine command or hook, and make the capture script exercise typed live search rather than only quick-pick navigation.

The shipped widget has a clean, compact presentation and the screencast demonstrates city switching, forecast opening, and return navigation. The forecast table is especially clear and matches the pinned NYC data in the shown flow. A stronger visual review would benefit from a fresh explicitly labeled desktop/mobile capture of the final build, but the delivered motion evidence and committed implementation are substantially complete.

The shipped widget has a clean, compact presentation and the screencast demonstrates city switching, forecast opening, and return navigation. The forecast table is especially clear and matches the pinned NYC data in the shown flow. A stronger visual review would benefit from a fresh explicitly labeled desktop/mobile capture of the final build, but the delivered motion evidence and committed implementation are substantially complete.

The shipped widget has a clean, compact presentation and the screencast demonstrates city switching, forecast opening, and return navigation. The forecast table is especially clear and matches the pinned NYC data in the shown flow. A stronger visual review would benefit from a fresh explicitly labeled desktop/mobile capture of the final build, but the delivered motion evidence and committed implementation are substantially complete.

Good extra touches like wind data, Fahrenheit conversion, and graceful handling of unknown cities show user‑centred thinking. Adding explicit UI controls for units would push this into the higher tier.

Clean, compact implementation with centralized forecast data and clear navigation/rendering helpers. Maintainability would improve by consolidating unit formatting and handling startup/data-load failures explicitly.

Clean, compact implementation with centralized forecast data and clear navigation/rendering helpers. Maintainability would improve by consolidating unit formatting and handling startup/data-load failures explicitly.

Good integration tests that verify the core flows and edge cases. Slight temperature value inconsistencies keep the score just below perfect.

Forecast data is correctly defined but reliance on a non‑existent external JSON for current weather breaks the single‑source principle, lowering the data score.

No agent configuration was provided; the repo contains only the widget implementation without any AGENTS.md or automation scripts, leading to a minimal agentic score.

Good functional implementation, but architectural separation could be improved by extracting data, view rendering, and server routing into distinct modules.

The only delivered visual evidence shows a persistent loading placeholder, not the required Rome, Bangkok Fahrenheit, or unknown-city rendered states, so the core weather experience could not be visually reviewed. The loading shell is clean and responsive, and the committed server markup suggests the intended result card is styled well, but the capture evidence is incomplete.

The only delivered visual evidence shows a persistent loading placeholder, not the required Rome, Bangkok Fahrenheit, or unknown-city rendered states, so the core weather experience could not be visually reviewed. The loading shell is clean and responsive, and the committed server markup suggests the intended result card is styled well, but the capture evidence is incomplete.

The only delivered visual evidence shows a persistent loading placeholder, not the required Rome, Bangkok Fahrenheit, or unknown-city rendered states, so the core weather experience could not be visually reviewed. The loading shell is clean and responsive, and the committed server markup suggests the intended result card is styled well, but the capture evidence is incomplete.

The page structure and scenario logic are reasonable, and the done note is present, but the committed product is broken because its required weather dataset is not included. Add the four-city data file (or embed the contract dataset) and rerun the scenario test.

A straightforward but thoughtful widget: the extra wind conversion, unit indicator, and polite recovery guidance make it more useful than the minimum brief. No especially memorable interaction or creative product feature is evident.

The code isolates data loading, but the required weather JSON file is missing from the repository, so the widget cannot source its data from the mandated dataset. Add the data/weather.json file containing the four cities and their weather to satisfy the data criterion.

The submitted done note is present, but the snapshot lacks the weather data file that server.js requires, making the widget non-runnable. Include the four-city dataset in the repository and simplify/separate the long HTML rendering path.

The submitted done note is present, but the snapshot lacks the weather data file that server.js requires, making the widget non-runnable. Include the four-city dataset in the repository and simplify/separate the long HTML rendering path.

Solid compact end-to-end coverage of every explicitly required scenario, but broaden assertions and add boundary/invalid-input tests for stronger regression protection.

Add an AGENTS.md (or equivalent) that tells an AI agent what the project is, how to run the server, and how to verify with the test. Include reusable scripts or hooks to automate those steps. This would raise the agentic score substantially.

Good separation of logic and presentation in a concise, well‑scoped file. The architecture matches the small scope of the widget.