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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Ship settings format v3 that deployed v2 readers can still read (forward/backward compatibility, atomic save, idempotent migration)

AClaude Haiku 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-17 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.02
Wall time
2m
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Task: settings format v3 without breaking deployed readers Upgrade `settings.py` to the v3 format in `FORMAT_V3.md`: `load(path)` reads v1, v2, v3 and newer-compatible files; `save(path, settings)` writes v3; add `migrate_dir(dir)` and an `UnsupportedVersion` exception class in `settings.py`. Files written by the new code must still be readable by the already-deployed `legacy_reader.py` (do not edit it). Standard library only. No network.

Must satisfy an unchangeable legacy reader (min_reader_version, legacy-safe theme value), preserve unknown keys at three levels, honour future versions, validate strictly (bool is not int), save atomically, and migrate idempotently with .bak copies. 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. All 9 hidden unittest cases pass: load v1/v2 with defaults, load v3 (theme_mode), exact v3 on-disk shape readable by the deployed legacy reader, round-trips, unknown keys preserved at top/appearance/notifications, future version handling and UnsupportedVersion, validation errors leave the existing file untouched with no temp files left, migrate_dir counts/.bak/idempotence, legacy_reader.py unchanged.

Setup notes: Use Case Scout batch 6 case f05-settings-v3-backcompat (offline fixture). Prepared with batch6/prepare.sh; hidden key/tests kept outside the agent's work dir. Prompt = TASK.md verbatim. Scored with the scout's scorer: `python score.py WORKDIR KEYDIR`. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Single run, no retries. Claude Code's own reported cost for claude-haiku-5.5: $0.024536. Score: 9/9. 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
$0.02
Wall time
2m
Human step-ins
0
Turns
6
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on208,06930,299$0.02

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Claude Haiku 5.5 (anthropic/claude-haiku-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. All 9 hidden unittest cases pass: load v1/v2 with defaults, load v3 (theme_mode), exact v3 on-disk shape readable by the deployed legacy reader, round-trips, unknown keys preserved at top/appearance/notifications, future version handling and UnsupportedVersion, validation errors leave the existing file untouched with no temp files left, migrate_dir counts/.bak/idempotence, legacy_reader.py unchanged.
  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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Evidence log
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 {
  "duration_api_ms": 122729,
  "stop_reason": "end_turn",
  "session_id": "[REDACTED]",
  "total_cost_usd": 0.02453639,
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   "cache_creation_input_tokens": 38448,
   "cache_read_input_tokens": 169609,
   "output_tokens": 30299,
   "output_tokens_details": {
    "thinking_tokens": 20998
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 38448,
    "ephemeral_5m_input_tokens": 0
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   "inference_geo": "global",
   "iterations": [
    {
     "input_tokens": 2,
     "output_tokens": 557,
     "cache_read_input_tokens": 50427,
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     "cache_creation": {
      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 560
     },
     "type": "message"
    }
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   "speed": "standard",
   "fallback_credit": null
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  "modelUsage": {
   "claude-haiku-5-5": {
    "inputTokens": 12,
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    "cacheReadInputTokens": 169609,
    "cacheCreationInputTokens": 38448,
    "webSearchRequests": 0,
    "costUSD": 0.02453639,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 20998,
    "canonicalModel": "claude-haiku-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,
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   "started_in_background": 0,
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   "spawned_by_subagents": 0,
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   "killed": {
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  "safety_stops": 0,
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  "num_turns": 6,
  "subtype": "success",
  "api_error_status": null,
  "result": "`settings.py` now reads v1, v2, v3 and compatible newer files, and writes v3. It also has `migrate_dir(dir)` and an `UnsupportedVersion` class. `legacy_reader.py` is untouched. My test script passes: it checks that every file `save` writes is read correctly by the deployed `legacy_reader.read`. The script lives in `/tmp/f05-tests/`, outside the work tree.\n\nDecisions the spec didn't settle:\n\n- **Newer-file version info** is kept in `extra[\"top\"]` as `version` and `min_reader_version`, and only for files with version > 3. This keeps the in-memory shape the same for v1\u2013v3 loads. `save` pops those keys back out and writes them. Otherwise it writes v3 with `min_reader_version: 2`.\n- **`min_reader_version` > 3 on any file**, including a v3 file, raises `UnsupportedVersion`. The spec only stated this for newer files, but the same rule applies.\n- **`migrate_dir` checks first, then writes.** It reads and validates every pre-v3 file before writing anything. An invalid file therefore aborts the run with no changes. A `.bak` that differs from the file's bytes raises `FileExistsError`. An identical `.bak` is reused without being overwritten.\n- **`save` ignores unknown top-level keys in the input dict**, rather than raising. Unknown keys belong in `extra`, so silently dropping them is a tradeoff you may want to change.\n- **Atomic write** uses a random temp name created with `O_EXCL` and mode 0666 under the umask. If the target exists, its mode is copied. The temp file is removed on any failure.",
  "ttft_ms": 1392,
  "type": "result",
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  "uuid": "[REDACTED]",
  "ttft_stream_ms": 1134,
  "time_to_request_ms": 271,
  "first_content_frame_ms": 1134,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

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