Claude Haiku 5.5 (effort default (no --effort flag) · thinking on) on Model ladder: fix 10 real merged bugs with tests hidden
AClaude Haiku 5.5default · thinking on · Claude Code 2.1.299 (headless -p) · cloud · 2026-10-16 · by @bobsiopener
- Estimated cost
- $0.0090
- Wall time
- 36s
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
You are working in a checkout of the python-humanize/humanize repository. A user filed this bug report: --- intcomma() raises OverflowError for very large integers `humanize.intcomma(10**400 + 123)` raises `OverflowError: int too large to convert to float` instead of returning the number with thousands separators. Negative huge integers (`-(10**400 + 123)`) fail the same way. Python ints are arbitrary precision, so I expect the full digits, correctly grouped (ending in `,123`), just like for small integers. --- Fix the bug in the library code. Dependencies are already installed (Python virtualenv in .venv; run tests with .venv/bin/pytest). Keep the change minimal and in the style of the codebase; you may add or update tests. Make sure the existing test suite still passes. You have no internet access.
Five real bug fixes merged into popular open-source libraries after the models' training cutoff (humanize, marshmallow, tenacity, nanoid, path-to-regexp). Each agent starts from the commit before the fix with only a symptom-style bug report, and the fix PR's own regression tests are applied afterwards to check the result. The size of the agent's source change is compared with the human fix. 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). Upstream fix being reproduced: https://github.com/python-humanize/humanize/pull/392, https://github.com/python-humanize/humanize/commit/984526c02448110a8392dde3f5e26096dfd7c729.
Success criteria: Hidden PR tests pass; existing suite stays green; diff under 2x the human diff size.
Setup notes: Real merged bug fix: python-humanize/humanize https://github.com/python-humanize/humanize/pull/392 (merged after the models' Jun 2026 cutoff). Agent got a history-free snapshot of the parent commit 14965a7495 with deps installed, and a symptom-only bug report written by the runner from the PR description (no fix hints). The PR's test files were overlaid only after the agent finished. Tools: Read/Write/Edit/Glob/Grep/Bash, web disabled. Diff-size flag (not scored): agent changed 17 source lines vs 2 in the human fix (allowance 20; within allowance). Claude Code's own reported cost for claude-haiku-5.5: $0.009041. Score: 2/2. 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
- $0.0090
- Wall time
- 36s
- Human step-ins
- 0
- Turns
- 9
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| AClaude Haiku 5.5anthropic/claude-haiku-5.5effort default (no --effort flag) · thinking on | 236,874 | 6,276 | $0.0090 |
Reproduce this run
- Use the use case prompt on the use case page.
- 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. - It counts as a success only if it meets every success criterion: Hidden PR tests pass; existing suite stays green; diff under 2x the human diff size.
- 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": 30882,
"stop_reason": "end_turn",
"session_id": "[REDACTED]",
"total_cost_usd": 0.00904065,
"usage": {
"input_tokens": 18,
"cache_creation_input_tokens": 18591,
"cache_read_input_tokens": 218265,
"output_tokens": 6276,
"output_tokens_details": {
"thinking_tokens": 3564
},
"server_tool_use": {
"web_search_requests": 0,
"web_fetch_requests": 0
},
"service_tier": "standard",
"cache_creation": {
"ephemeral_1h_input_tokens": 18591,
"ephemeral_5m_input_tokens": 0
},
"inference_geo": "global",
"iterations": [
{
"input_tokens": 2,
"output_tokens": 532,
"cache_read_input_tokens": 30553,
"cache_creation_input_tokens": 577,
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 577
},
"type": "message"
}
],
"speed": "standard",
"fallback_credit": null
},
"modelUsage": {
"claude-haiku-5-5": {
"inputTokens": 18,
"outputTokens": 6276,
"cacheReadInputTokens": 218265,
"cacheCreationInputTokens": 18591,
"webSearchRequests": 0,
"costUSD": 0.00904065,
"contextWindow": 1000000,
"maxOutputTokens": 128000,
"thinkingTokens": 3564,
"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,
"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": 9,
"subtype": "success",
"api_error_status": null,
"result": "`intcomma()` now returns full, correctly grouped output for huge integers, both positive and negative, instead of raising `OverflowError`.\n\n**Cause:** `intcomma` called `float(value)` on every non-string input just to check for NaN/inf. For ints beyond float range, that raises `OverflowError`. Strings had a related bug: `float(\"1\"*400)` quietly returns `inf`, so `intcomma(\"1\"*400)` produced `+Inf`.\n\n**Fix** (`src/humanize/number.py`, `intcomma`):\n- Integer strings (optional sign, digits only) are parsed with `int()` directly.\n- Non-string inputs skip the float check when they're already `int`. Floats and other types keep the finiteness check, so NaN/inf and `None` behave as before.\n- Non-integer strings keep the existing path, so `\"nan\"` \u2192 `NaN`, `\"1e5\"` \u2192 `1e5`, and `\"abc\"` \u2192 `abc` are unchanged.\n\n**Tests** (`tests/test_number.py`): added cases for `10**400 + 123` and its negative, both as int and as string.\n\n**Results:**\n- `intcomma(10**400+123)` and `intcomma(-(10**400+123))` both end in `00,000,123`.\n- `.venv/bin/pytest --ignore=tests/test_benchmarks.py`: 713 passed, 110 skipped.\n- The full run also reports 15 errors in `tests/test_benchmarks.py`. These happen without my change too (checked with `git stash`); the `benchmark` fixture isn't available in this environment, so I left them alone.",
"ttft_ms": 1626,
"type": "result",
"duration_ms": 34998,
"uuid": "[REDACTED]",
"ttft_stream_ms": 1193,
"time_to_request_ms": 215,
"first_content_frame_ms": 1193,
"queued_turn_count": 0,
"result_index": 0
}
]