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Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Implement a reader/writer for a documented chunked binary container (LEB128 lengths, CRC-32, zlib chunks, critical vs ancillary)

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
$0.01
Wall time
1m
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Task: implement the CHNK container format Implement `read(buf)` and `write(...)` in `chnk.py` exactly as documented in `FORMAT.md` (including every error case and its `.offset`). Keep the `FormatError(msg, offset)` class. Python standard library only (`zlib` is fine). No network.

Every error path has an exact expected byte offset; minimal-varint and 5-byte limits, CRC over type+payload, META ordering, PNG-style critical/ancillary rule and byte-exact writer output are each tested. 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 12 hidden unittest cases pass: basic read, no-CRC + META merge, ancillary skipping, multi-byte varints, header errors, truncation offsets, type errors, varint errors, CRC mismatches, semantic errors, byte-exact writer output, 120 random read(write()) round-trips.

Setup notes: Use Case Scout batch 6 case f10-chunked-binary-format (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: $0.013495. Score: 12/12. 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
$0.01
Wall time
1m
Human step-ins
0
Turns
7
Model usage
ModelInput tokOutput tokCost
AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on186,95314,836$0.01

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 12 hidden unittest cases pass: basic read, no-CRC + META merge, ancillary skipping, multi-byte varints, header errors, truncation offsets, type errors, varint errors, CRC mismatches, semantic errors, byte-exact writer output, 120 random read(write()) round-trips.
  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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  "session_id": "[REDACTED]",
  "total_cost_usd": 0.013495009999999998,
  "usage": {
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   "cache_read_input_tokens": 164801,
   "output_tokens": 14836,
   "output_tokens_details": {
    "thinking_tokens": 7710
   },
   "server_tool_use": {
    "web_search_requests": 0,
    "web_fetch_requests": 0
   },
   "service_tier": "standard",
   "cache_creation": {
    "ephemeral_1h_input_tokens": 22138,
    "ephemeral_5m_input_tokens": 0
   },
   "inference_geo": "global",
   "iterations": [
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      "ephemeral_5m_input_tokens": 0,
      "ephemeral_1h_input_tokens": 2660
     },
     "type": "message"
    }
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   "speed": "standard",
   "fallback_credit": null
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  "modelUsage": {
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    "webSearchRequests": 0,
    "costUSD": 0.013495009999999998,
    "contextWindow": 1000000,
    "maxOutputTokens": 128000,
    "thinkingTokens": 7710,
    "canonicalModel": "claude-haiku-5-5",
    "provider": "firstParty",
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   }
  },
  "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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  "num_turns": 7,
  "subtype": "success",
  "api_error_status": null,
  "result": "I implemented `read(buf)` and `write(...)` in `chnk.py`. `FormatError(msg, offset)` is unchanged. The round-trip and error-case tests I ran all pass, and the test script lives in `/tmp/chnk_tests/`, outside the work directory. This isn't a git repo, so I didn't commit anything.\n\nWhere FORMAT.md left room, I chose the stricter reading:\n\n- **META:** an empty META payload, a trailing `\\n`, or an empty line is rejected as a bad META line. A key containing no `=` or an empty key is rejected too.\n- **DATZ:** the stream must be complete, with no trailing bytes after it. A truncated or padded zlib stream is \"bad zlib data\" at the chunk's offset.\n- **Writer:** it raises `ValueError` for inputs it can't represent: an empty key, a key containing `=` or a newline, a value containing a newline, `chunk_size < 1`, or a chunk longer than the 5-byte varint limit. FORMAT.md doesn't cover these, so they are my addition.\n- **Missing END:** when the input ends exactly at a chunk boundary, the error is at `len(input)`. A chunk cut off partway is reported at that chunk's start.\n\nIf you want the looser reading for any of these, say so and I'll change it.",
  "ttft_ms": 1316,
  "type": "result",
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  "uuid": "[REDACTED]",
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  "time_to_request_ms": 243,
  "first_content_frame_ms": 1065,
  "queued_turn_count": 0,
  "result_index": 0
 }
]

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