Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Build a TV home screen that shows a smart home's device status instead of ads

AClaude Sonnet 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-20 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.12
Wall time: 52s
Human step-ins: 0
Outcome: Pass

Compare with other models on this task →

Exact prompt

# TV home screen for a (synthetic) smart home `home.json` describes one synthetic home: `as_of`, `local_utc_offset_hours`, `night`, `offline_after_minutes`, `temp_drift_f`, `rooms` (display order) and `devices`. Only these listed devices exist; nothing is contacted. Write `solve.py` (Python 3 standard library only, no network). `python solve.py input.json answer.json` (first argument unused; read `home.json` from the current directory) writes `answer.json` and `home.html`. Fresh homes are generated when scoring. ## Rules 1. Timestamps carry their own offsets (`Z`, `-04:00`, `-07:00`, `+01:00` ...); compare instants, not wall-clock text. 2. A device is `offline` when as_of - last_seen > `offline_after_minutes` (strictly), else `online`. 3. Tile state (`data-state`) for an online device: light/plug `on`|`off`; lock `locked`|`unlocked`; contact `open`|`closed`; leak `wet`|`dry`; camera `recording`|`idle`; thermostat = current temperature in Fahrenheit with 1 decimal (e.g. `68.5`). Celsius values convert as F = C x 9/5 + 32, rounded half-up to 1 decimal (do the same for setpoints). An offline device's state is `unknown`. 4. It is night when the local hour of as_of (using `local_utc_offset_hours`) is >= night.start_hour or < night.end_hour. 5. Alerts (offline devices raise only `offline`, nothing else). Kinds, in severity order: `leak` (leak sensor wet), `unlocked_at_night` (lock unlocked at night), `door_open` (contact open and as_of - open_since > 30 min), `offline`, `temp_drift` (|current F - setpoint F| > temp_drift_f, both 1-decimal F values), `low_battery` (battery not null and < 20). One device can raise several alerts. 6. Alert order: severity, then the device's room position in `rooms`, then device name (case-insensitive), then id. 7. Summary: `lights_on` (online lights that are on), `online`, `offline`, `alerts` (count), `avg_temp_f` (mean of online thermostats' 1-decimal F values, rounded half-up to 1 decimal; null if none). 8. Room slug: lower-case, every run of non-alphanumeric characters becomes `-`, leading/trailing `-` removed (`Kid's Room` -> `kid-s-room`). ## answer.json `{"rooms": [{"name", "slug", "devices": [{"id", "status", "state"}] sorted by name case-insensitive}] in rooms order, "alerts": [{"device": id, "kind"}] in alert order, "summary": {"lights_on", "online", "offline", "alerts", "avg_temp_f"}}` ## Visual output: home.html (a 1920x1080 TV screen) Static and self-contained: no `<script>`, `<img>`, `<link>`, `<iframe>`/`<object>`/`<embed>`, `on*` handlers, external URLs, CSS url(http)/@import or fetches. - One `<section id="room-<slug>">` per room, in `rooms` order, containing one element `id="dev-<id>"` per device with `data-status` and `data-state` as above. - An element `id="alerts"` containing one element `id="alert-1"`, `id="alert-2"`, ... per alert in order, each with `data-device` and `data-kind`. - An element `id="summary"` with `data-lights-on`, `data-online`, `data-offline`, `data-alerts`, `data-avg-temp-f` (1 decimal, or `none`). - In a 1920x1080 browser viewport the page must fit without scrolling, `#alerts` must be fully on screen, and every device tile must be at least 40x40 px and on screen. Styling is otherwise up to you. ## Scoring Hidden checks (partial credit; all must pass): `html_static_rooms_in_order`, `device_tiles_status_state`, `alerts_rules_and_order`, `summary_counts`, `browser_fits_1080p_no_network` (headless browser, network blocked) on the given home; `fresh_run_1`, `fresh_run_2` (answer.json and home.html on new homes). 30-second limit per run.

The page looks right long before the data is right: one naive timestamp parse flips several devices online/offline and changes every alert, count and tile. Original benchmark task written for usecaserank.com (not based on a specific public post). Headless, offline run on a reproducible fixture. Each run's notes say how its cost was measured (estimates are marked).

Success criteria: 1. html_static_rooms_in_order 2. device_tiles_status_state 3. alerts_rules_and_order 4. summary_counts 5. browser_fits_1080p_no_network 6. fresh_run_1 7. fresh_run_2

Setup notes: Use Case Scout batch 13 case n01-tv-home-screen (offline, synthetic fixture). Prepared with batch13/prepare.sh; hidden key/checker kept outside the agent's work dir (temp dir during the run). Prompt = TASK.md verbatim. Scored with the case's scorer: `python score.py WORKDIR KEYDIR` (python3, run from the case dir). Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. 1-min load average at scoring 5.68 (8 cores). home.html rendered offline with google-chrome headless (CDP pipe, network blocked): PNG 1920x1080 at ~3 s after load; MP4 ~6 s captured at 1920x1080, H.264 1280x720. Claude Code's own reported cost for claude-sonnet-5.5: $0.12073. Score: 7/7. Cost is an ESTIMATE: measured tokens x pricing.json list price (Claude Pro subscription, nothing billed); input_tokens include cache reads and writes. Single run.

Estimated cost List-price estimate; not actually billed.

Output

Metrics

Estimated cost: $0.12
Wall time: 52s
Human step-ins: 0
Turns: 4

Model usage
Model	Input tok	Output tok	Cost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on	95,285	4,856	$0.12

Reproduce this run

Use the use case prompt on the use case page.
Same setup: Claude Sonnet 5.5 (anthropic/claude-sonnet-5.5, effort default (no --effort flag) · thinking on) via Claude Code 2.1.299 (headless -p), cloud.
It counts as a success only if it meets every success criterion: 1. html_static_rooms_in_order 2. device_tiles_status_state 3. alerts_rules_and_order 4. summary_counts 5. browser_fits_1080p_no_network 6. fresh_run_1 7. fresh_run_2
Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.

How runs are scored: Methodology.

Was this useful?

⇄ Rerun on another model

Automated checks

Trust 80% comes from these checks (how Trust % works).

Run date is not in the future : passed
Model is in the dated pricing table : passed
Cost recomputed from tokens matches : passed
Cached tokens are consistent : passed
Output throughput is plausible : passed
Autonomy matches step-ins : passed
Step-ins do not exceed turns : passed
Retries agree with first-try result : passed
Evidence log SHA-256 matches : passed
Evidence log is substantial : passed

Evidence log

[
 {
  "duration_api_ms": 51063,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.1207299,
  "usage": {
   "input_tokens": 8,
   "cache_creation_input_tokens": 16058,
   "cache_read_input_tokens": 79219,
   "output_tokens": 4856,
   "output_tokens_details": {
    "thinking_tokens": 751
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 16058,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 671,
     "cache_read_input_tokens": 23828,
     "cache_creation_input_tokens": 4769,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 4769
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 8,
    "outputTokens": 4856,
    "cacheReadInputTokens": 79219,
    "cacheCreationInputTokens": 16058,
    "webSearchRequests": 0,
    "costUSD": 0.1207299,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 751,
    "canonicalModel": "claude-sonnet-5-5",
    "provider": "firstParty",
    "costBasis": "list"
   }
  },
  "permission_denials": [],
  "terminal_reason": "completed",
  "fast_mode_state": "off",
  "fast_mode_disabled_reason": "sdk_opt_in_required",
  "subagent_stats": {
   "spawned": 0,
   "requested": {
    "background": 0,
    "foreground": 0,
    "unset": 0
   },
   "started_in_background": 0,
   "max_depth": 0,
   "spawned_by_subagents": 0,
   "completed": 0,
   "failed": 0,
   "killed": {
    "parent": 0,
    "user": 0,
    "system": 0
   },
   "refused": {
    "depth_limit": 0,
    "concurrency_limit": 0,
    "budget": 0
   },
   "by_type": {}
  },
  "safety_stops": 0,
  "is_error": false,
  "num_turns": 4,
  "subtype": "success",
  "api_error_status": null,
  "result": "I wrote `solve.py` in the working directory. On the given `home.json` it runs cleanly and writes `answer.json` and `home.html`. I only checked the JSON output. I did not open `home.html` in a browser, so the 1920x1080 fit is unchecked.\n\nOn this home the output is:\n- **Devices:** 26 devices, 21 online and 5 offline.\n- **Alerts:** 10, in this order: two leaks (`d08`, `d21`), five offline (`le-11`, `co-15`, `d13`, `li-16`, `d24`), two `temp_drift` (`d03`, `d05`) and one `low_battery` (`d02`).\n- **Summary:** 1 light on, average temperature 68.9\u00b0F.\n- **Night alerts:** `as_of` is 19:58 local, so it isn't night and no `unlocked_at_night` alerts fire.\n\n- **Missing `open_since`:** Nothing in this home has `open_since`, so I couldn't see where it lives. The script reads it from either the device's `state` or the device itself. An open contact with no `open_since` raises no `door_open` alert, and that path is untested here.\n- **Layout:** The page has fixed 1920x1080 dimensions with `overflow:hidden`. The alerts panel is a 4-column grid with room for about 36 alerts, and the room sections use a 4-column grid. A very large home could be clipped.\n- **`avg_temp_f` format:** In `answer.json` it is written as a number (68.9). It is `null` if there are no online thermostats, and `none` in the HTML.",
  "ttft_ms": 13876,
  "type": "result",
  "duration_ms": 51547,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 13481,
  "time_to_request_ms": 284,
  "first_content_frame_ms": 13481,
  "queued_turn_count": 0,
  "result_index": 0
 }
]