Claude Opus 5.5 (effort default (no --effort flag) · thinking on) on Make a stdlib Python service pass its healthcheck (4 layered config bugs)

AClaude Opus 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-16 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first tryCompare

Estimated cost: $0.14
Wall time: 31s
Human step-ins: 0
Outcome: Pass

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Exact prompt

# Task: get the service healthy This directory has a small Python service (`svc/app.py`), its config, data, `.env`, `run.sh` (starts it) and `healthcheck.sh`. Right now `./run.sh && ./healthcheck.sh` fails. Make it pass. Rules: do NOT edit `healthcheck.sh` or the `/health` handler in `app.py`; don't hard-code the health response; the service must still read config from `config.toml`, the token from `.env`, and items from `data/items.json`. Fix root causes, not symptoms. When done, stop the service (`kill $(cat .pid)`) and write `FIXES.md` listing each problem you found (one line each). Python stdlib only, no network.

Get a small Python web service to pass its health check without touching the check itself. Four layered configuration bugs (an environment-variable typo, a port stored as a string, a relative data path and a JSON trailing comma) surface one at a time. The scorer confirms the health response reflects live data, so hard-coding it fails. 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. healthcheck.sh must be byte-identical to the original. 2. The /health handler block in app.py must be unchanged (text compare). 3. After ./run.sh, ./healthcheck.sh must exit 0 (service on 127.0.0.1:18080 returns status ok with the original item count). 4. Anti-hardcoding: the scorer appends a 4th item to data/items.json, restarts the service, and /health must report 4 items (data then restored). 5. FIXES.md must list at least 4 problems (lines starting with -, * or a digit).

Setup notes: Use Case Scout batch 3 case c09-broken-service (offline fixture). Prepared with batch3/prepare.sh; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored with the scout's scorer: `bash score.sh WORKDIR`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Claude Code's own reported cost for claude-opus-5.5: $0.140975. Score: 4/4 checks. 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.

Metrics

Estimated cost: $0.14
Wall time: 31s
Human step-ins: 0
Turns: 6

Model usage
Model	Input tok	Output tok	Cost
AClaude Opus 5.5anthropic/claude-opus-5.5effort default (no --effort flag) · thinking on	119,585	2,155	$0.14

Reproduce this run

Use the use case prompt on the use case page.
Same setup: Claude Opus 5.5 (anthropic/claude-opus-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. healthcheck.sh must be byte-identical to the original. 2. The /health handler block in app.py must be unchanged (text compare). 3. After ./run.sh, ./healthcheck.sh must exit 0 (service on 127.0.0.1:18080 returns status ok with the original item count). 4. Anti-hardcoding: the scorer appends a 4th item to data/items.json, restarts the service, and /health must report 4 items (data then restored). 5. FIXES.md must list at least 4 problems (lines starting with -, * or a digit).
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).

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": 29332,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.1409754,
  "usage": {
   "input_tokens": 12,
   "cache_creation_input_tokens": 9476,
   "cache_read_input_tokens": 110097,
   "output_tokens": 2155,
   "output_tokens_details": {
    "thinking_tokens": 278
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 9476,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 409,
     "cache_read_input_tokens": 20800,
     "cache_creation_input_tokens": 822,
     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 822
     },
     "type": "message"
    }
   ],
   "speed": "standard",
   "fallback_credit": null
  },
  "modelUsage": {
   "claude-opus-5-5": {
    "inputTokens": 12,
    "outputTokens": 2155,
    "cacheReadInputTokens": 110097,
    "cacheCreationInputTokens": 9476,
    "webSearchRequests": 0,
    "costUSD": 0.1409754,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 278,
    "canonicalModel": "claude-opus-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": 6,
  "subtype": "success",
  "api_error_status": null,
  "result": "`./run.sh && ./healthcheck.sh` now passes: the healthcheck got `{\"status\": \"ok\", \"items\": 3}` and exited 0. I've stopped the service and confirmed it no longer responds, and `FIXES.md` is written.\n\nThere were four problems:\n\n1. **`.env`**: the variable was misspelled `APP_TOKN`, so the app crashed at startup looking for `APP_TOKEN`. I renamed it.\n2. **`svc/config.toml`**: `port` was the string `\"18080\"`, so the port range check crashed. I changed it to the number `18080`.\n3. **Data path**: `data_dir = \"data\"` was read relative to the folder the app runs from (`svc/`), so it pointed at `svc/data`, which doesn't exist. I set it to `../data`. I also changed `load_config()` in `app.py` so this path is always taken relative to where `config.toml` lives, wherever the app is started from.\n4. **`data/items.json`**: a trailing comma after the last item made the file invalid JSON. I removed it.\n\nI didn't touch `healthcheck.sh` or the `/health` handler. The service still reads its config from `config.toml`, the token from `.env` and the items from `data/items.json`.",
  "ttft_ms": 2917,
  "type": "result",
  "duration_ms": 30603,
  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1552,
  "time_to_request_ms": 221,
  "first_content_frame_ms": 1553,
  "queued_turn_count": 0,
  "result_index": 0
 }
]