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Claude Sonnet 5.5 (effort default (no --effort flag) · thinking on) on Life-like automaton from RLE with a Klein-bottle grid and a playable animated page

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

Trust 80%Fully autonomoussuccess · first trySuperseded
Estimated cost
$0.07
Wall time
49m
Human step-ins
0
Outcome
Pass

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Superseded. This run was rescored on 2026-10-20 and replaced by a newer run. It no longer counts toward rankings, use-case tables or the data export; it is kept here for the record.

Summary

Exact prompt

# Life-like cellular automaton from an RLE file, with a playable page `input.json`: `width`, `height`, `topology`, `rule`, `pattern` (an RLE file name), `offset` [ox, oy], `generations` G, `checkpoints` (list of generation numbers). Write `solve.py` (Python 3 standard library only); `python solve.py input.json answer.json` must write `answer.json` and `life.html` in the working directory. Fresh inputs are generated. ## RLE grammar (full) 1. Lines whose first non-blank character is `#` are comments. Blank lines are ignored. 2. The first non-comment line is the header `x = m, y = n[, rule = ...]`. Ignore its values; the rule always comes from `input.json`. 3. The remaining lines are concatenated with line breaks removed. Everything after the first `!` is ignored, even if it looks like more pattern. 4. Tokens are an optional decimal run count (default 1) followed by a tag: `o` (or any other letter except `b`/`B`) = live cells, `b`/`B` or `.` = dead cells, `$` = end of row. A count on `$` skips that many rows: `3$` moves down 3 rows and resets x to 0. Missing trailing dead cells in a row are implied. 5. Pattern cell (x, y) is placed at grid cell (x+ox, y+oy). For `torus`/`klein`, wrap that position with modulo width/height. For `bounded`, drop cells that fall outside the grid. ## Rule string 6. `Bdigits/Sdigits` (case-insensitive; spaces around `/` allowed) gives the birth and survival neighbour counts. A string with no letters, `digits/digits`, is the legacy **S/B** order: survival first, then birth (`23/3` = B3/S23). Either digit list may be empty. ## Topology (8-neighbour Moore neighbourhood) 7. `bounded`: cells outside the grid are always dead. `torus`: both axes wrap. `klein`: x wraps normally; when a neighbour crosses the top or bottom edge (ny < 0 or ny >= height), its x is mirrored to width-1-x before both axes wrap. A neighbour position that appears more than once counts more than once. (This happens only on tiny grids, never in the tests.) 8. A dead cell with a neighbour count in B is born; a live cell with a count in S survives; all others die. Updates are simultaneous. ## answer.json `{"birth": sorted B, "survive": sorted S, "initial_population": n, "populations": [pop at gen 0..G], "cells_at": {"<g>": [[x, y], ...] for each checkpoint, sorted by y then x}}` ## life.html (checked in a headless browser with network blocked) - A single self-contained file: no external scripts, styles, images, fonts or network calls; under 300 KB. Embedding the initial cells is fine. - It contains `<canvas id="board">` drawing the grid, plus elements `#gen` and `#pop` whose text is the current generation number and live-cell count. - On load it starts animating at least 4 generations per second. - It exposes `window.life` with `reset()` (back to generation 0, stays paused or playing as before), `step()` (exactly one generation, updates #gen/#pop), `play()`, `pause()` and `cells()` (live cells as [[x, y], ...] sorted by y then x). It must use the same rules, topology and placement as above. ## Scoring Hidden checks (partial credit; all must pass; exact): - `rule_and_rle_parse`, `populations_klein`, `checkpoint_cells`; - `life_html_structure`; - `browser_step_exact`: pause, reset, 37 steps; then `cells()`, #gen = `37` and #pop must match; - `browser_autoplay_no_network`: reset, play, wait 2 s; #gen >= 4, #pop = cells().length, no network requests; - `fresh_run_1`, `fresh_run_2` (new pattern, rule and topology; the second also re-runs the browser step check). 40-second limit per run.

Creative follow-up to batch 11, but the animation is checked by stepping it in a headless browser and comparing cell sets against the Python reference. 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. rule_and_rle_parse 2. populations_klein 3. checkpoint_cells 4. life_html_structure 5. browser_step_exact 6. browser_autoplay_no_network 7. fresh_run_1 8. fresh_run_2

Setup notes: Use Case Scout batch 12 case m12-life-rle-animation (offline, synthetic fixture). Prepared with batch12/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 0.19 (8 cores). life.html rendered offline with google-chrome headless (CDP pipe, network blocked): PNG 1280x800 at ~3 s after load; MP4 ~6 s captured at 1280x720, H.264 1280x720. Claude Code's own reported cost for claude-sonnet-5.5: $0.071734. Score: 8/8. 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
$0.07
Wall time
49m
Human step-ins
0
Turns
3
Model usage
ModelInput tokOutput tokCost
AClaude Sonnet 5.5anthropic/claude-sonnet-5.5effort default (no --effort flag) · thinking on63,6514,739$0.07

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. 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.
  3. It counts as a success only if it meets every success criterion: 1. rule_and_rle_parse 2. populations_klein 3. checkpoint_cells 4. life_html_structure 5. browser_step_exact 6. browser_autoplay_no_network 7. fresh_run_1 8. fresh_run_2
  4. 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.

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Automated checks

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

Evidence log
[
 {
  "duration_api_ms": 521594,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.0717338,
  "usage": {
   "input_tokens": 8,
   "cache_creation_input_tokens": 11291,
   "cache_read_input_tokens": 71577,
   "output_tokens": 4746,
   "output_tokens_details": {
    "thinking_tokens": 1210
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 11291,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 500,
     "cache_read_input_tokens": 20592,
     "cache_creation_input_tokens": 3238,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 3238
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-sonnet-5-5": {
    "inputTokens": 6,
    "outputTokens": 4739,
    "cacheReadInputTokens": 59038,
    "cacheCreationInputTokens": 4607,
    "webSearchRequests": 0,
    "costUSD": 0.0717338,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 1210,
    "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
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   "refused": {
    "depth_limit": 0,
    "concurrency_limit": 0,
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   "by_type": {}
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  "safety_stops": 0,
  "is_error": false,
  "num_turns": 3,
  "subtype": "success",
  "api_error_status": null,
  "result": "I wrote `solve.py`. Running `python solve.py input.json answer.json` on the sample input (54\u00d748 klein, B36/S23) produced `answer.json` and a 2,904-byte `life.html`. That is the only run I did, and it is also the only check on `answer.json`: its first values look plausible (B [3, 6], S [2, 3], initial population 94, 160 generations of populations). I haven't compared `answer.json` against any reference. I also haven't opened `life.html` in a browser, so `window.life`, the 37-step check and autoplay are untested.\n\n- **Parsing:** it follows the RLE and rule grammar you gave, and reads the pattern file from the path in `input.json` or from next to that file. A string like `23/3` is read as legacy S/B order.\n- **Topology:** neighbour counts handle bounded, torus and klein, including the x-mirror across the top and bottom edges. The page uses the same neighbour logic.\n- **Page:** `life.html` is one self-contained file with `<canvas id=\"board\">`, `#gen` and `#pop`. It autoplays at 10 generations per second and exposes `window.life` with `reset`, `step`, `play`, `pause` and `cells`. The initial cells are embedded.",
  "ttft_ms": 501177,
  "type": "result",
  "duration_ms": 522105,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1092,
  "time_to_request_ms": 274,
  "first_content_frame_ms": 1092,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

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