Eval Report

Case	Condition	Result	Pass/Total	Cost	Time	Input Tok	Output Tok	Cache Read	Cache Create	API Calls	Cost Delta	Time Delta	Failure Reason
nanobot-exectool-regex	baseline	PASS	1/1	$0.14	50s	181,446	1,833	165,387	16,049	7	—	—
	cli-v0.0.2	PASS	1/1	$0.20	70s	326,910	2,787	308,787	18,106	14	+43%	+41%
nanobot-streaming-metadata	baseline	PASS	1/1	$0.44	158s	1,208,666	10,935	1,131,551	76,964	45	—	—
	cli-v0.0.3	PASS	1/1	$0.37	92s	480,241	5,300	436,872	43,352	18	-16%	-42%
pydantic-importstring-error	baseline	PASS	1/1	$0.39	163s	537,340	9,514	511,366	25,952	19	—	—
	cli-v0.0.2	PASS	1/1	$0.39	180s	438,303	11,072	412,478	25,807	16	+0%	+10%
fastapi-optional-file-list	baseline	PASS	1/1	$0.50	183s	1,958,665	12,620	1,892,603	65,945	68	—	—
	cli-v0.0.2	PASS	1/1	$0.47	104s	902,535	5,522	870,182	32,319	29	-6%	-43%
langchain-merge-parallel-tools	baseline	PASS	1/1	$0.55	237s	704,733	12,079	659,724	44,988	21	—	—
	cli-v0.0.2	PASS	1/1	$0.50	187s	707,035	9,776	664,971	42,043	20	-9%	-21%
autogen-serialization-data-loss	baseline	PASS	1/1	$0.71	295s	1,779,880	18,382	1,716,179	62,706	74	—	—
	cli-v0.0.3	PASS	1/1	$0.66	199s	1,165,689	11,181	1,123,705	41,950	34	-7%	-32%
autogen-provider-namespace-restriction	baseline	PASS	1/1	$0.65	450s	1,078,420	13,464	1,020,004	58,367	40	—	—
llamaindex-async-postprocess	baseline	FAIL	0/1	$0.76	252s	1,441,531	17,046	1,358,990	82,458	57	—	—	exit: error_api
	cli-v0.0.3	PASS	1/1	$0.76	216s	1,254,596	15,954	1,149,085	105,407	62	+0%	-14%
llamaindex-run-id-passthrough	baseline	FAIL	0/1	$0.84	234s	2,067,692	15,653	1,960,130	106,834	68	—	—	exit: error_api
vercel-ai-oauth-trailing-slash	baseline	PASS	1/1	$0.71	200s	1,312,184	9,889	1,264,399	47,753	31	—	—
	cli-v0.0.3	PASS	1/1	$0.75	216s	1,354,814	10,771	1,302,023	51,885	32	+6%	+8%
vercel-ai-error-code	baseline	PASS	1/1	$1.96	739s	5,559,656	48,696	5,381,292	178,243	105	—	—
	cli-v0.0.2	PASS	1/1	$1.29	369s	2,322,092	19,063	2,232,260	89,790	43	-34%	-50%

nanobot-exectool-regex

baseline — PASS — $0.14 — 50s

Metric	Tokens	Note
Cache read	165,387	0.1x cost weight
Cache create	16,049	1.25x cost weight
Output (total)	1,833	5x cost weight
Thinking	1,768	96% of output
Non-thinking	65	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,004	8	259c	think(19tok): Let me explore the codebase to find the shell tool's workspace safety guard.
2	3.1s	16,217	228	40	8,047c	Read nanobot/agent/tools/shell.py
3	6.7s	16,445	2,486	8	17,190c	think(102tok): The bug is clear. In `_extract_absolute_paths`, the Windows path regex `r"[A-Za-
4	7.0s	18,931	5,932	2	111c	text(38tok): Now I have a clear picture. The fix is in line 189 of `shell
5	7.6s	24,863	322	2	118c	text(5tok): Now add the tests:
6	5.4s	25,185	705	3	1,041c	text(8tok): Now let me verify the tests pass:
7	9.3s	25,890	753	1	1,373c	text(15tok): Also run the full test suite to make sure nothing regressed:
8	—	26,643	619	1	0c	text(222tok): All 43 tests pass. Here's what was done: Root cause: In
SUM	39.0s	165,387	16,049	65	28,139c

cli-v0.0.2 — PASS — $0.20 — 70s

Metric	Tokens	Note
Cache read	308,787	0.1x cost weight
Cache create	18,106	1.25x cost weight
Output (total)	2,787	5x cost weight
Thinking	2,248	81% of output
Non-thinking	539	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,138	8	2,474c	think(19tok): Let me start by reading the root NODE.md to understand the project structure.
2	6.3s	16,351	861	59	3,470c	Read agent/NODE.md
3	2.5s	16,351	1,902	61	2,679c	Read agent/tools/NODE.md
4	1.9s	17,212	1,926	67	104c	Read agent/tools/shell.py
5	3.1s	19,138	138	65	88c	Glob '**/shell.py'
6	2.8s	19,276	143	71	8,047c	Read nanobot/agent/tools/shell.py
7	7.3s	19,419	2,484	8	14c	think(159tok): I can see the issue. In `_extract_absolute_paths`, the Windows path regex is: ``
8	2.6s	21,903	372	66	33c	Glob '*/testexec*'
9	2.4s	22,275	119	46	2,926c	Read tests/tools/test_exec_security.py
10	3.9s	22,394	1,191	1	111c	text(37tok): Now I have all the context I need. The fix is simple: change
11	9.8s	23,585	312	2	116c	text(11tok): Now add tests for the bare drive-root case:
12	4.6s	23,897	712	3	1,916c	text(12tok): Now let me run the new tests to verify they pass:
13	11.6s	24,609	973	8	116c	think(195tok): The test `test_guard_allows_workspace_path_windows` is failing because on Linux,
14	2.3s	25,582	600	73	1,288c	Bash: python -m pytest tests/tools/test_exec_security.py -v 2>&1 \| tail -20
15	—	25,582	1,235	1	0c	text(185tok): All 8 tests pass. Here's a summary of what was done: **Root
SUM	61.0s	308,787	18,106	539	23,382c

nanobot-streaming-metadata

baseline — PASS — $0.44 — 158s

Metric	Tokens	Note
Cache read	1,131,551	0.1x cost weight
Cache create	76,964	1.25x cost weight
Output (total)	10,935	5x cost weight
Thinking	10,160	93% of output
Non-thinking	775	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$0.27	371,732	5,371	350,177	21,538
claude-haiku-4-5-20251001	$0.18	836,934	5,564	781,374	55,426

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,061	8	0c	think(32tok): Let me explore the codebase to understand the structure and find the relevant co
2	2.1s	0	13,904	3	1,740c	Bash: find /tmp/ct-eval-nanobot-streaming-metadata-a2M9I7 -type f -name "*.py" \| head
3	1.7s	13,904	1,377	1	303c	Bash: find /tmp/ct-eval-nanobot-streaming-metadata-a2M9I7 -type d -name "src" -o -type
4	1.0s	13,904	1,638	70	1,356c	Bash: ls -la /tmp/ct-eval-nanobot-streaming-metadata-a2M9I7/
5	1.1s	15,281	1,128	70	968c	Bash: ls -la /tmp/ct-eval-nanobot-streaming-metadata-a2M9I7/nanobot/
6	0.2s	15,542	1,539	1	1,385c	Grep 'streaming\|stream\|metadata\|message_thread' in nanobot
7	0.2s	17,081	824	1	17,462c	Read nanobot/cli/stream.py
8	0.4s	17,905	6,275	1	11,899c	Read nanobot/channels/manager.py
9	0.5s	24,180	3,642	6	7,437c	Read nanobot/channels/base.py:300L
10	2.2s	27,822	2,384	1	1,221c	Bash: grep -n "send_delta\\|metadata\\|_stream_\\|message_thread_id" /tmp/ct-eval-nanobot
11	1.7s	30,206	545	3	3,816c	Read nanobot/channels/feishu.py:100L
12	1.6s	30,206	1,975	38	8,392c	Read nanobot/channels/feishu.py@980:150L
13	2.4s	32,181	2,541	1	161c	Grep 'OutboundMessage\|_stream_delta\|_stream_en' in nanobot/agent
14	0.3s	34,722	228	59	9,309c	Read nanobot/agent/loop.py:150L
15	2.3s	34,722	3,326	3	5,546c	Read nanobot/agent/loop.py@300:100L
16	0.1s	34,950	4,731	1	6,337c	Read nanobot/agent/loop.py@440:80L
17	2.3s	39,681	2,263	1	148c	Bash: grep -n "_FeishuStreamBuf\\|@dataclass" /tmp/ct-eval-nanobot-streaming-metadata-a
18	1.2s	41,944	201	45	1,251c	Read nanobot/channels/feishu.py@260:30L
19	1.5s	41,944	725	1	96c	Grep 'message_thread_id\|thread_id\|root_id' in nanobot
20	1.5s	42,669	190	50	848c	Bash: grep -n "thread_id\\|root_id\\|message_thread_id" /tmp/ct-eval-nanobot-streaming-m
21	1.6s	42,669	570	1	879c	Bash: find /tmp/ct-eval-nanobot-streaming-metadata-a2M9I7/tests -name "*.py" -type f \|
22	2.0s	43,239	483	45	11,721c	Read tests/channels/test_channel_manager_delta_coalescing.py
23	2.1s	43,722	3,594	1	44c	Bash: grep -n "_handle_message" /tmp/ct-eval-nanobot-streaming-metadata-a2M9I7/nanobot
24	1.4s	47,316	241	59	1,956c	Read nanobot/channels/feishu.py@1295:40L
25	18.2s	47,316	952	1	6,759c	Bash: grep -n "class OutboundMessage\\|class InboundMessage" /tmp/ct-eval-nanobot-strea
26	5.4s	16,274	2,495	8	3,655c	think(131tok): Now I have a comprehensive understanding of the codebase. Let me look at the spe
27	6.6s	18,769	1,215	8	2,623c	think(170tok): I can see the bug now. In `on_stream` (lines 323-331) and `on_stream_end` (lines
28	4.8s	19,984	1,174	8	39c	think(131tok): Now I can see the pattern. The final response (lines 481-486) does `meta = dict(
29	2.1s	21,158	286	66	538c	Glob 'tests/agent/*/.py'
30	2.4s	21,444	293	59	3,414c	Read tests/agent/test_runner.py:80L
31	2.1s	21,444	1,502	63	2,585c	Read tests/agent/test_task_cancel.py:60L
32	12.5s	22,946	943	10	2,101c	think(276tok): Now I have enough context to make the fix. Let me look at the exact lines in loo
33	6.7s	23,889	1,513	2	108c	text(11tok): Now I'll apply the fix and write the test:
34	3.4s	25,402	689	4	5,482c	text(25tok): Now let me write the test. First, let me check how `_dispatc
35	7.5s	26,091	2,295	8	2,831c	think(229tok): I can see from `test_task_cancel.py` that `_dispatch` is tested by mocking `_pro
36	17.7s	28,386	1,300	8	120c	think(102tok): Now I have enough to write the test. Let me check what `_process_message` signat
37	3.5s	29,686	1,605	58	804c	Bash: python -m pytest tests/agent/test_loop_streaming_metadata.py -v 2>&1
38	6.1s	31,291	909	1	259c	text(44tok): Both tests pass. The Pyright warnings are type-checker noise
39	—	32,200	258	1	0c	text(228tok): All 177 agent tests pass. ## Summary Root cause: In `n
SUM	130.5s	1,083,283	76,814	775	125,593c

cli-v0.0.3 — PASS — $0.37 — 92s

Metric	Tokens	Note
Cache read	436,872	0.1x cost weight
Cache create	43,352	1.25x cost weight
Output (total)	5,300	5x cost weight
Thinking	4,841	91% of output
Non-thinking	459	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,226	8	2,736c	think(19tok): Let me start by reading the root NODE.md to understand the project structure.
2	0.1s	16,439	944	69	7,363c	Read bus/NODE.md
3	0.1s	17,383	2,143	9	235c	think(38tok): Now let me look at the bus events.py to understand InboundMessage and OutboundMe
4	0.3s	17,383	2,465	55	28c	Glob '*/.py'
5	3.0s	19,848	236	54	4,291c	Bash: find /tmp/ct-eval-nanobot-streaming-metadata-vgZA3x -name "*.py" \| head -50
6	3.5s	19,848	2,103	62	5,724c	Bash: find /tmp/ct-eval-nanobot-streaming-metadata-vgZA3x -name "*.py" \| grep -v tests
7	2.6s	20,084	4,342	58	10,347c	Bash: find /tmp/ct-eval-nanobot-streaming-metadata-vgZA3x -name ".py" -not -path "/.
8	0.6s	24,426	4,628	53	30,472c	Read nanobot/bus/events.py
9	16.9s	29,054	9,110	8	108c	think(340tok): Now I can see the bug. In `_dispatch` (lines 308-364), when `_wants_stream` is i
10	2.8s	38,164	1,410	4	2,880c	text(25tok): Now let me write tests. Let me first look at an existing age
11	4.2s	39,574	1,525	8	12,925c	think(57tok): The diagnostics are pre-existing (not introduced by my change). Now let me look
12	26.3s	41,099	4,382	8	115c	think(160tok): Now I understand the test patterns. Let me write tests for the streaming metadat
13	4.0s	45,481	2,259	53	1,012c	Bash: .venv/bin/python -m pytest tests/agent/test_streaming_metadata.py -v 2>&1
14	6.1s	47,740	1,396	8	2,952c	text(72tok): All 4 tests pass. The Pyright warnings in the test file are
15	—	49,136	1,183	2	0c	text(231tok): All 179 tests pass. ## Summary Root cause: In `nanobot
SUM	70.5s	436,872	43,352	459	81,188c

pydantic-importstring-error

baseline — PASS — $0.39 — 163s

Metric	Tokens	Note
Cache read	511,366	0.1x cost weight
Cache create	25,952	1.25x cost weight
Output (total)	9,514	5x cost weight
Thinking	8,907	94% of output
Non-thinking	607	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,157	8	148c	think(22tok): Let me explore the codebase to understand how `ImportString` is implemented in p
2	2.6s	16,370	199	51	4,320c	Grep 'ImportString\|import_string' in pydantic/types.py
3	4.4s	16,569	1,423	55	2,506c	Grep 'import_string' in pydantic/_internal/_validators.py
4	4.6s	16,569	2,286	34	3,371c	Read pydantic/_internal/_validators.py@79:60L
5	70.8s	18,855	1,113	8	16c	think(1861tok): Now I can see the two bugs: 1. Bug 1 (broken internal import): When `import
6	4.2s	19,968	5,642	48	284c	Bash: grep -rn "import_string\\|ImportString\\|_import_string" /tmp/ct-eval-pydantic-imp
7	2.6s	25,610	235	59	16c	Grep 'import_string\\|ImportString' in tests/test_utils.py
8	2.7s	25,845	132	68	905c	Bash: grep -n "import_string\\|ImportString" /tmp/ct-eval-pydantic-importstring-error-7
9	2.5s	25,977	390	46	3,878c	Read tests/test_types.py@970:90L
10	14.0s	26,367	1,370	8	121c	think(44tok): Now I have a good understanding of the two bugs and how to fix them. Let me also
11	3.1s	27,737	851	1	1,563c	text(29tok): Now let's add tests. I need a helper module with a broken in
12	2.4s	28,588	695	62	25c	Bash: ls /tmp/ct-eval-pydantic-importstring-error-7soVt9/tests/types/
13	3.5s	29,283	100	1	1,563c	text(28tok): I'll add a test fixture module and two new test cases to `te
14	2.9s	29,383	699	45	1,094c	Read tests/test_types.py@1055:25L
15	13.8s	30,082	500	4	107c	text(41tok): Now I'll add the two tests. I'll use `sys.modules` manipulat
16	5.3s	30,582	1,153	6	1,077c	text(12tok): Now let's run the new tests to verify they pass:
17	3.5s	31,735	957	1	1,984c	text(24tok): Both tests pass. Let me also run the existing import-string
18	3.7s	32,692	930	54	1,487c	Bash: python -m pytest tests/test_types.py -k "import_string or ImportString" -v --ign
19	3.3s	33,622	697	47	3,588c	Bash: python -m pytest tests/test_types.py -k "string_import" -xvs 2>&1
20	—	34,319	1,423	1	0c	text(265tok): All existing tests pass. Here's a summary of what was done:
SUM	150.0s	511,366	25,952	607	28,053c

cli-v0.0.2 — PASS — $0.39 — 180s

Metric	Tokens	Note
Cache read	412,478	0.1x cost weight
Cache create	25,807	1.25x cost weight
Output (total)	11,072	5x cost weight
Thinking	10,639	96% of output
Non-thinking	433	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,354	0	3,098c	think(32tok): Let me start by reading the root NODE.md to understand the project structure, th
2	0.7s	16,567	1,010	69	5,030c	Read types/NODE.md
3	6.6s	17,577	1,680	8	1,000c	think(18tok): Let me look at the `ImportString` implementation in pydantic/types.py.
4	2.6s	19,257	430	52	234c	Grep 'import_string\|import_path' in pydantic/_internal/_validators.py
5	2.7s	19,257	640	51	3,706c	Read pydantic/_internal/_validators.py@65:70L
6	78.2s	19,687	1,432	8	905c	think(2255tok): Now I can see the two bugs: 1. Bug 1: When `import_module(module_path)` rai
7	3.2s	21,119	6,166	59	4,338c	Read tests/test_types.py@964:100L
8	30.8s	27,285	1,398	8	937c	think(575tok): Now I understand the full picture. Let me fix the bugs: 1. **Bug 1 (broken inte
9	6.6s	28,683	2,483	59	121c	Edit pydantic/_internal/_validators.py
10	2.8s	31,166	583	1	1,449c	text(17tok): Now let me add tests. Let me find where to add them in the t
11	2.8s	31,749	611	1	1,132c	text(14tok): Now let me check the imports at the top of the test file:
12	9.6s	32,360	463	65	107c	Edit tests/test_types.py
13	5.6s	32,823	867	3	1,086c	text(12tok): Now let's run the new tests to verify they pass:
14	4.5s	33,690	943	1	1,479c	text(25tok): Both tests pass. Let me also run the existing `ImportString`
15	4.1s	34,633	779	47	2,305c	Bash: python -m pytest tests/test_types.py -k "string_import" -v 2>&1 \| tail -30
16	—	35,412	968	1	0c	text(301tok): All existing tests pass. Here's a summary of the fix: ## Ch
SUM	160.7s	412,478	25,807	433	26,927c

fastapi-optional-file-list

baseline — PASS — $0.50 — 183s

Metric	Tokens	Note
Cache read	1,892,603	0.1x cost weight
Cache create	65,945	1.25x cost weight
Output (total)	12,620	5x cost weight
Thinking	11,406	90% of output
Non-thinking	1,214	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$0.24	420,599	4,049	404,123	16,455
claude-haiku-4-5-20251001	$0.25	1,538,066	8,571	1,488,480	49,490

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,079	8	0c	think(33tok): Let me explore the codebase to understand the structure and find the relevant co
2	2.3s	0	13,928	7	1,896c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 -type f -name "*.py" \| grep
3	1.5s	13,928	1,483	1	54c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 -type d -name "fastapi" \| he
4	1.0s	15,411	136	53	1,326c	Glob '/tmp/ct-eval-fastapi-optional-file-list-5PYqS3/fastapi/*.py'
5	1.5s	15,411	707	1	226c	Grep 'issubclass' in fastapi
6	1.5s	15,547	808	1	4,678c	Grep 'issubclass.*(?:File\|Upload\|bytes\|List\|Se' in fastapi
7	1.2s	16,355	2,056	1	8,110c	Read fastapi/_compat/shared.py
8	2.3s	16,355	4,900	1	2,092c	Grep 'is_bytes_sequence_annotation\|is_uploadfi' in fastapi/dependencies/utils.py
9	1.8s	21,255	854	1	709c	Bash: grep -n "lenient_issubclass\\|issubclass" /tmp/ct-eval-fastapi-optional-file-list
10	1.3s	22,109	392	1	192c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -type f -name "file"
11	1.4s	22,501	209	4	1,529c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -type f -name "*.py" \|
12	1.3s	22,501	949	65	906c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -type f -name "*.py" -
13	1.8s	22,710	1,225	1	31c	Bash: grep -r "Optional\[List\[bytes\]\]" /tmp/ct-eval-fastapi-optional-file-list-5PYq
14	1.6s	23,935	286	1	1,543c	Read fastapi/_compat/shared.py@169:30L
15	1.2s	24,221	601	1	1,033c	Read fastapi/_compat/shared.py@77:16L
16	1.7s	24,822	439	4	67c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -name "*.py" \| xargs g
17	0.9s	24,822	610	69	5,427c	Read tests/test_compat.py
18	4.9s	25,432	1,969	2	567c	Bash: python3 << 'EOF' from typing import Optional, List, Union, get_origin, get_args
19	2.1s	27,401	694	1	264c	Bash: grep -rn "is_bytes_sequence_annotation\\|is_uploadfile_sequence_annotation" /tmp/
20	1.1s	28,095	347	59	1,819c	Read fastapi/dependencies/utils.py@450:25L
21	3.1s	28,095	946	1	26c	Bash: python3 << 'EOF' from typing import Optional, List from fastapi import FastAPI,
22	1.5s	29,041	224	7	31c	Bash: grep -r "Optional.List.File\\|File.Optional.List" /tmp/ct-eval-fastapi-option
23	1.7s	29,265	149	1	339c	Bash: grep -r "TypeError.*issubclass" /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/
24	1.7s	29,265	388	3	31c	Bash: grep -rn "issubclass" /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/fastapi --i
25	2.7s	29,653	158	5	331c	Bash: grep -rn " issubclass(" /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/fastapi -
26	1.3s	29,653	505	1	1,312c	Read fastapi/_compat/v2.py@365:20L
27	1.7s	30,158	543	1	1,190c	Bash: grep -rn "serialize_sequence_value" /tmp/ct-eval-fastapi-optional-file-list-5PYq
28	2.4s	30,701	633	1	1,260c	Read fastapi/dependencies/utils.py@900:20L
29	1.5s	31,334	496	5	2,059c	Read fastapi/dependencies/utils.py@880:40L
30	3.3s	31,830	739	1	809c	Bash: grep -rn "def is_bytes_sequence_field\\|is_bytes_sequence_field" /tmp/ct-eval-fas
31	1.4s	32,569	579	59	813c	Read fastapi/_compat/v2.py@359:10L
32	3.9s	32,569	946	1	318c	Bash: python3 << 'EOF' from typing import Optional, List, Union, get_origin, get_args
33	2.3s	33,515	519	2	13c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -name "*.py" -type f \|
34	1.3s	34,034	263	64	31c	Bash: grep -r "serialize_sequence_value" /tmp/ct-eval-fastapi-optional-file-list-5PYqS
35	1.6s	34,297	117	1	2,297c	Read fastapi/_compat/v2.py@1:50L
36	1.8s	34,414	897	1	852c	Read fastapi/_compat/v2.py@370:10L
37	3.3s	35,311	536	2	788c	Bash: python3 << 'EOF' from typing import Optional, List, get_origin from fastapi._com
38	1.6s	35,847	580	1	407c	Bash: grep -A5 -B5 "def serialize_sequence_value" /tmp/ct-eval-fastapi-optional-file-l
39	1.8s	36,427	265	1	131c	Bash: git -C /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 log --all --oneline --grep
40	1.3s	36,692	196	67	824c	Bash: git -C /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 log --all --oneline \| grep
41	1.7s	36,888	373	5	315c	Bash: git -C /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 show 27cc3408 --stat \| hea
42	1.2s	36,888	610	1	108c	Read tests/test_file/test_nullable_and_defaults.py@1:100L
43	1.3s	37,498	291	58	264c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -name "nullable" -o
44	2.3s	37,789	218	59	91c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -path "test_file" -t
45	1.4s	38,007	139	1	79c	Bash: git -C /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 log --oneline --all \| head
46	1.6s	38,146	136	61	856c	Bash: git -C /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 log --oneline \| grep -i "o
47	1.4s	38,282	407	4	63c	Bash: git -C /tmp/ct-eval-fastapi-optional-file-list-5PYqS3 status \| head -20
48	1.5s	38,689	128	5	169c	Bash: find /tmp/ct-eval-fastapi-optional-file-list-5PYqS3/tests -name "*.py" -type f \|
49	1.4s	38,817	221	45	2,943c	Read tests/test_file_and_form_order_issue_9116.py
50	2.4s	39,038	1,287	1	496c	Bash: grep -A10 -B10 "Optional.List.bytes\\|List.*bytes" /tmp/ct-eval-fastapi-optiona
51	8.0s	40,325	307	1	10,834c	Bash: python3 << 'EOF' """ Test to demonstrate the bug with Optional[List[bytes]] and
52	4.2s	16,292	1,332	8	1,312c	think(90tok): Now I need to look at the actual code to understand the exact fix needed, and al
53	3.0s	17,624	648	33	251c	Grep 'get_args\|get_origin' in fastapi/_compat/v2.py
54	3.9s	18,272	231	1	1,819c	text(56tok): The fix requires unwrapping the `Optional`/`Union` type befo
55	4.5s	18,503	765	2	44c	text(55tok): Now I understand the fix. In `serialize_sequence_value`, we
56	2.1s	19,268	180	71	2,943c	Read tests/test_file_and_form_order_issue_9116.py
57	8.0s	19,448	1,185	10	2,139c	think(185tok): Now I have all the information I need. Let me: 1. Fix the bug in `/tmp/ct-eval-
58	3.5s	20,633	1,183	8	473c	think(23tok): I need to also check if `UnionType` is available. Let me check how `shared.py` h
59	2.7s	21,816	418	62	48c	Grep 'UnionType' in fastapi/types.py
60	5.0s	22,234	147	1	108c	text(13tok): Now I have everything I need. Let me apply the fix:
61	2.6s	22,381	477	54	16c	Grep 'UnionType' in fastapi/_compat/may_v1.py
62	3.8s	22,858	786	8	1,173c	think(25tok): `UnionType` is not in `may_v1` module. Let me check what's in that module and fi
63	2.9s	22,858	1,372	59	108c	Edit fastapi/_compat/v2.py
64	2.5s	24,230	220	72	264c	Grep 'UnionType' in fastapi/_compat/shared.py
65	3.8s	24,230	565	8	1,069c	think(59tok): `shared.UnionType` - let me check if it's exported from `shared.py`. I saw it's
66	7.1s	24,795	509	1	109c	text(9tok): Good. Now let me write the test file:
67	2.9s	25,304	632	66	621c	Bash: python -m pytest tests/test_optional_file_list.py -v 2>&1
68	3.5s	25,936	292	1	870c	text(24tok): Both tests pass. Let me also run the existing file upload te
69	—	26,228	434	1	0c	text(204tok): All tests pass. Here's a summary of the changes: **Root cau
SUM	164.1s	1,851,971	62,844	1,214	75,916c

cli-v0.0.2 — PASS — $0.47 — 104s

Metric	Tokens	Note
Cache read	870,182	0.1x cost weight
Cache create	32,319	1.25x cost weight
Output (total)	5,522	5x cost weight
Thinking	4,855	88% of output
Non-thinking	667	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,216	8	2,292c	think(19tok): Let me start by reading the root NODE.md to understand the project structure.
2	1.9s	16,429	770	69	3,412c	Read core/NODE.md
3	0.3s	17,199	1,033	8	11,916c	think(26tok): Let me look at the routing NODE.md and the actual routing code to understand how
4	4.0s	18,232	3,849	8	1,326c	think(28tok): Let me look for the routing.py file and find where the TypeError: issubclass() a
5	2.4s	22,081	615	38	4,089c	Grep 'issubclass' in fastapi
6	2.7s	22,696	1,561	13	8,110c	think(33tok): Let me look at the `_compat/shared.py` file in more detail, specifically around
7	4.3s	24,257	2,769	9	4,988c	think(32tok): Now let me look at how these functions are used in the dependencies/utils.py fil
8	2.1s	27,026	1,588	66	4,547c	Read fastapi/dependencies/utils.py@730:100L
9	3.9s	28,614	1,617	38	16c	Grep 'request_body_to_args\\|serialize_sequence' in fastapi/dependencies/utils.py
10	2.6s	30,231	157	38	16c	Grep 'bytes_sequence\\|file.*sequence\\|sequence' in fastapi
11	2.6s	30,388	161	41	16c	Grep 'is_bytes_sequence_annotation\\|is_uploadf' in fastapi
12	2.2s	30,549	142	72	16c	Grep 'is_bytes_sequence_annotation\\|is_uploadf' in /tmp/ct-eval-fastapi-optional-file-list-WtWhKM
13	3.8s	30,691	139	24	2,835c	think(56tok): Hmm, these functions are defined in shared.py but not called anywhere? Let me lo
14	0.4s	30,830	1,141	8	2,568c	think(206tok): Found it! The bug is at line 374 in `fastapi/_compat/v2.py`: ```python def seri
15	0.6s	31,971	1,389	8	2,703c	think(18tok): Now let me also look at the v1 implementation to understand the pattern:
16	9.0s	33,360	1,235	8	1,934c	think(412tok): Now I understand the bug. In `fastapi/_compat/v2.py`, line 372-375: ```python d
17	3.4s	34,595	1,311	8	48c	think(47tok): Now I need to check if `UnionType` is imported in v2.py. Let me check. From the
18	5.0s	35,906	222	1	108c	text(31tok): The `UnionType` is available from `fastapi._compat.shared` (
19	3.6s	36,128	525	2	473c	text(18tok): Now I need to make `UnionType` accessible from `shared`. Let
20	3.9s	36,653	920	1	3,843c	text(46tok): `UnionType` is already imported and used in `shared.py`. The
21	2.2s	36,653	2,151	56	98c	Glob '/tmp/ct-eval-fastapi-optional-file-list-WtWhKM/tests/test_file.py'
22	0.1s	38,804	238	72	2,957c	Glob '/tmp/ct-eval-fastapi-optional-file-list-WtWhKM/tests/test_upload.py'
23	6.3s	39,042	1,299	1	109c	text(20tok): Now I have a good understanding of the test pattern. Let me
24	4.9s	40,341	517	66	823c	Bash: python -m pytest tests/test_optional_file_list.py -v 2>&1
25	3.5s	40,858	396	1	1,072c	text(22tok): Both tests pass. Let me also quickly verify the fix didn't b
26	—	41,254	539	1	0c	text(334tok): All tests pass. Here's a summary of the fix: ## Root Cause
27	—	41,793	595	1	0c	text(19tok): The background task confirmed the tests completed successful
28	—	42,388	224	1	0c	text(10tok): All tests passing. The fix is complete.
SUM	75.9s	870,182	32,319	667	60,315c

langchain-merge-parallel-tools

baseline — PASS — $0.55 — 237s

Metric	Tokens	Note
Cache read	659,724	0.1x cost weight
Cache create	44,988	1.25x cost weight
Output (total)	12,079	5x cost weight
Thinking	11,624	96% of output
Non-thinking	455	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	0.6s	11,213	7,272	8	1,418c	think(20tok): Let me explore the codebase to find the relevant code for streaming tool calls.
2	2.8s	18,485	769	35	2,206c	Grep 'def merge_lists\|def _merge_tool\|merge_di' in .
3	2.1s	18,485	1,695	40	9,009c	Read libs/core/langchain_core/utils/_merge.py
4	7.0s	20,180	2,547	8	9,792c	think(176tok): Now I understand the code. The `merge_lists` function in `_merge.py` handles mer
5	5.6s	22,727	3,182	9	2,818c	think(22tok): Now let me look at the `__add__` method of `AIMessageChunk` to see how chunks ar
6	2.9s	25,909	1,052	54	3,086c	Read libs/core/langchain_core/messages/ai.py@658:80L
7	19.2s	25,909	2,162	13	15,128c	think(549tok): Now I understand the code flow. The key is in `merge_lists` in `_merge.py`. When
8	1.2s	28,071	5,737	8	3,150c	think(563tok): Now I understand the bug. Looking at `merge_lists`: ```python def merge_lists(l
9	3.0s	33,808	2,103	50	4,801c	Grep 'tool_call_chunk.index\|index.tool_call_' in libs/core/tests/unit_tests/test_messages.py
10	1.0s	33,808	3,916	8	4,891c	think(1278tok): Now I understand the issue better. Let me look at what happens when parallel too
11	39.8s	37,724	5,749	8	2,987c	think(754tok): Now let me look more at the `merge_lists` function and how it handles tool_call_
12	4.1s	43,473	3,410	59	131c	Edit libs/core/langchain_core/utils/_merge.py
13	3.4s	46,883	365	4	181c	text(19tok): Now let me add tests. First, let me find where the tool call
14	2.4s	47,248	357	72	2,414c	Read libs/core/tests/unit_tests/test_messages.py@859:60L
15	4.0s	47,605	975	73	668c	Read libs/core/tests/unit_tests/test_messages.py@917:10L
16	11.1s	48,580	335	2	134c	text(22tok): Now I'll add tests for the parallel tool call bug and sequen
17	34.0s	48,915	1,017	1	1,797c	text(12tok): Now let's run the tests to verify the fix works:
18	4.2s	49,932	837	1	3,936c	text(23tok): Test passes. Let me also run the existing merge-related test
19	—	50,769	1,508	2	0c	text(300tok): All 207 tests pass. Here's a summary of the changes: **Root
SUM	148.4s	659,724	44,988	455	68,547c

cli-v0.0.2 — PASS — $0.50 — 187s

Metric	Tokens	Note
Cache read	664,971	0.1x cost weight
Cache create	42,043	1.25x cost weight
Output (total)	9,776	5x cost weight
Thinking	9,309	95% of output
Non-thinking	467	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	7,418	8	2,368c	think(33tok): Let me start by reading the root NODE.md to understand the project structure, th
2	2.4s	18,631	812	69	2,958c	Read core/NODE.md
3	0.9s	19,443	948	8	2,209c	think(40tok): I need to find the code that handles streaming tool calls and merging. Let me lo
4	2.7s	20,391	1,014	50	724c	Glob '*/messages/.py'
5	2.5s	21,405	356	64	31,818c	Read libs/core/langchain_core/messages/ai.py
6	5.8s	21,405	9,866	8	40c	think(46tok): The key is in `add_ai_message_chunks` function, specifically in the `merge_lists
7	3.0s	31,271	207	46	9,009c	Read libs/core/langchain_core/utils/_merge.py
8	0.9s	31,271	2,754	9	3,914c	think(1460tok): Now I understand the issue. Let me trace through the bug: In `merge_lists`, whe
9	2.8s	34,025	7,164	69	4,320c	Read libs/core/tests/unit_tests/messages/test_ai.py@100:100L
10	10.9s	41,189	1,545	1	131c	text(162tok): Now I have enough context. The bug is clear: Root cause
11	2.9s	42,734	635	1	14c	text(18tok): Now let me write the tests. First, let me look at existing m
12	2.7s	42,734	767	46	736c	Glob '*/tests/unit_tests/utils/.py'
13	3.7s	43,369	525	8	14c	think(30tok): There doesn't seem to be a dedicated test file for `_merge.py`. Let me check if
14	7.4s	43,894	186	8	11,496c	think(150tok): No existing test file for `merge_lists`. I'll add tests in `test_ai.py` for the
15	4.1s	44,080	4,172	2	582c	text(12tok): Now I'll add tests at the end of `test_ai.py`:
16	12.5s	48,252	395	59	137c	Edit libs/core/tests/unit_tests/messages/test_ai.py
17	5.4s	48,647	1,045	8	3,202c	text(12tok): Now let's run the tests to verify the fix works:
18	24.0s	49,692	1,633	1	1,463c	text(38tok): All 16 tests pass. The diagnostics are pre-existing issues u
19	—	51,325	601	2	0c	text(319tok): All 1697 tests pass. Here's a summary of the changes: ---
SUM	94.6s	664,971	42,043	467	75,135c

autogen-serialization-data-loss

baseline — PASS — $0.71 — 295s

Metric	Tokens	Note
Cache read	1,716,179	0.1x cost weight
Cache create	62,706	1.25x cost weight
Output (total)	18,382	5x cost weight
Thinking	17,005	93% of output
Non-thinking	1,377	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$0.55	955,644	10,604	925,205	30,407
claude-haiku-4-5-20251001	$0.16	824,236	7,778	790,974	32,299

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,156	8	0c	think(23tok): Let me explore the codebase to understand the structure and find the affected mo
2	2.2s	12,608	1,354	8	2,196c	Bash: find /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5 -type f -name "*.py" \|
3	0.0s	13,962	1,486	1	1,445c	Grep 'class (GroupChatMessage\|GroupChatStart\|G' in /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5
4	0.1s	13,962	2,352	1	33,607c	Read python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py
5	0.0s	16,314	9,693	1	459c	Grep 'model_validator\|field_serializer\|field_v' in python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat
6	0.4s	26,007	1,372	45	2,480c	Read python/packages/autogen-agentchat/tests/test_group_chat.py
7	0.1s	27,379	1,168	1	7,491c	Bash: grep -r "model_dump_json\\|model_validator\\|field_serializer" /tmp/ct-eval-autoge
8	0.0s	27,379	4,111	1	68c	Bash: grep -n "GroupChatMessage\\|model_dump" /tmp/ct-eval-autogen-serialization-data-l
9	0.4s	31,490	406	3	1,325c	Bash: grep -A 20 "class GroupChatMessage" /tmp/ct-eval-autogen-serialization-data-loss
10	0.4s	31,896	637	1	1,295c	Bash: grep -B 5 -A 15 "class BaseMessage" /tmp/ct-eval-autogen-serialization-data-loss
11	0.5s	32,533	655	1	3,691c	Read python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py:114L
12	0.2s	33,188	1,420	1	397c	Bash: find /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/packages/autogen
13	0.3s	34,608	557	69	1,490c	Bash: grep -B 5 -A 20 "^class Response" /tmp/ct-eval-autogen-serialization-data-loss-2
14	4.0s	34,608	1,240	1	197c	Bash: find . -name pytest.ini -o -name setup.py -o -name pyproject.toml \| head -5
15	3.7s	35,848	180	59	130c	Bash: python3 -c " from autogen_agentchat.messages import TextMessage from autogen_age
16	2.3s	36,028	301	1	1,146c	Bash: find /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5 -name "test" -type f
17	1.6s	36,329	578	63	443c	Bash: ls -la /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/packages/autog
18	2.1s	36,907	351	8	31c	Bash: grep -n "model_dump\\|serialize" /tmp/ct-eval-autogen-serialization-data-loss-2Ih
19	0.3s	37,258	248	5	954c	Bash: head -30 /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/packages/aut
20	0.3s	37,506	540	1	62c	Bash: grep -n "pydantic" /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/pa
21	1.9s	38,046	314	5	403c	Bash: find /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/packages/autogen
22	0.0s	38,360	309	1	1,013c	Bash: grep -r "discriminator\\|Field(discriminator" /tmp/ct-eval-autogen-serialization-
23	2.1s	38,669	713	1	1,186c	Read python/packages/autogen-agentchat/src/autogen_agentchat/messages.py@647:25L
24	5.6s	39,382	522	5	637c	Bash: cat > /tmp/test_serialization.py << 'EOF' """ This script demonstrates the seria
25	14.8s	39,904	899	1	6,510c	Bash: cat > /tmp/test_abstract_serialization.py << 'EOF' """ This script demonstrates
26	0.7s	16,369	2,155	9	7,410c	think(104tok): Now I have a clear understanding of the bug. Let me look at the actual files to
27	0.7s	18,524	2,511	39	251c	Grep '^ChatMessage\s=\|^AgentEvent\s=\|^Intern' in python/packages/autogen-agentchat/src/autogen_agentchat/messages.py
28	0.2s	21,035	431	67	8,996c	Read python/packages/autogen-agentchat/src/autogen_agentchat/messages.py@640:50L
29	48.1s	21,466	3,006	8	329c	think(945tok): Now I understand the full picture. The issue is: 1. `GroupChatMessage.message`
30	3.7s	24,472	3,293	38	2,156c	Read python/packages/autogen-agentchat/tests/test_group_chat.py:50L
31	16.4s	27,765	824	8	176c	think(424tok): Now I have all the information I need. Let me make the changes: 1. Fix `_events
32	2.7s	28,589	1,230	67	176c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py
33	3.8s	29,819	381	72	176c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py
34	3.1s	30,200	254	1	176c	text(21tok): Now `BaseChatMessage` is no longer needed in `_events.py`. L
35	4.7s	30,454	355	8	694c	think(82tok): Wait, Pyright is saying `BaseChatMessage` is not accessed, but we removed it fro
36	5.6s	30,809	422	8	161c	think(35tok): The import looks fine. Pyright diagnostics may be stale. Let me proceed with the
37	5.5s	31,231	426	72	161c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/base/_task.py
38	2.8s	31,657	359	47	888c	think(51tok): Pyright says `AgentEvent` and `ChatMessage` are not accessed - but they should b
39	3.6s	32,016	451	8	167c	think(33tok): The changes look correct. The Pyright diagnostics might be stale or wrong. Now
40	4.0s	32,467	325	72	167c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/base/_chat_agent.py
41	6.3s	32,792	405	27	1,223c	think(112tok): Pyright says they're not accessed but we're using them in the dataclass fields.
42	5.0s	33,197	613	8	1,191c	think(43tok): The changes look correct. Now I need to write tests. Let me find where to place
43	3.1s	33,810	622	62	1,783c	Read python/packages/autogen-agentchat/tests/test_messages.py:50L
44	13.3s	33,810	1,281	1	149c	text(7tok): Now I'll write the test file:
45	3.7s	35,091	1,242	3	1,579c	text(9tok): Now let's run the tests to verify:
46	2.7s	36,333	791	66	342c	Bash: cd /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/packages/autogen-a
47	5.5s	36,333	1,006	66	31c	Bash: pip install -e . -q --break-system-packages 2>&1 \| tail -10
48	3.2s	37,339	109	61	389c	Bash: cd /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5 && find . -name "*.pth" -
49	3.0s	37,448	302	66	138c	Bash: cd /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/packages/autogen-a
50	4.2s	37,750	202	66	487c	Bash: cd /tmp/ct-eval-autogen-serialization-data-loss-2IhtW5/python/packages/autogen-a
51	3.2s	37,750	515	66	135c	Bash: .venv/bin/python -m pip install pytest -q && .venv/bin/python -m pytest tests/te
52	3.5s	38,265	181	66	1,170c	Bash: PYTHONPATH=src python -m pytest tests/test_event_serialization.py -v 2>&1
53	5.5s	38,265	671	2	2,090c	text(21tok): All 5 tests pass. Let me also quickly verify the existing te
54	—	38,936	888	1	0c	text(263tok): All tests pass. Here's a summary of the changes: **Root cau
SUM	211.4s	1,675,376	61,813	1,377	101,447c

cli-v0.0.3 — PASS — $0.66 — 199s

Metric	Tokens	Note
Cache read	1,123,705	0.1x cost weight
Cache create	41,950	1.25x cost weight
Output (total)	11,181	5x cost weight
Thinking	10,074	90% of output
Non-thinking	1,107	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,296	8	2,488c	think(33tok): Let me start by reading the root NODE.md to understand the project structure, th
2	2.2s	16,509	822	62	5,643c	Read agentchat/NODE.md
3	1.3s	17,331	1,663	8	50c	think(23tok): Let me look at the messages.py file and the group chat implementation to underst
4	3.1s	18,994	335	61	5,401c	Bash: find /tmp/ct-eval-autogen-serialization-data-loss-xZk4x5 -name "*.py" \| head -50
5	3.1s	18,994	2,577	56	1,622c	Bash: find /tmp/ct-eval-autogen-serialization-data-loss-xZk4x5/python -name "*.py" \| x
6	2.4s	21,571	780	53	3,660c	Read python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py
7	4.5s	22,351	1,225	8	119c	think(108tok): Now I see the issue. The `GroupChatMessage` has a `message` field typed as `Base
8	2.3s	23,576	279	72	27,539c	Read python/packages/autogen-agentchat/src/autogen_agentchat/messages.py
9	9.9s	23,855	8,261	8	249c	think(224tok): Now I understand the issue. The problem is in `_events.py`: 1. `GroupChatMessag
10	0.5s	32,116	648	59	6,985c	Read python/packages/autogen-agentchat/src/autogen_agentchat/base/_chat_agent.py
11	0.7s	32,764	2,239	8	47c	think(1023tok): Now I understand the full picture. The issue is: 1. `GroupChatMessage`: `me
12	0.3s	35,003	2,302	66	1,153c	Bash: find /tmp/ct-eval-autogen-serialization-data-loss-xZk4x5/python -name "pyproject
13	22.6s	37,305	731	8	4,070c	think(494tok): Good, Pydantic 2.x is being used. `SerializeAsAny` is available in Pydantic v2.
14	3.3s	38,036	2,961	8	2,006c	think(33tok): Now let me look at how `Response` is used in specific places to understand if it
15	29.5s	40,997	1,027	8	2,278c	think(814tok): Now I have a clear picture. Here's my plan: 1. `_events.py` - Fix `GroupCha
16	2.6s	42,024	2,776	45	1,783c	Read python/packages/autogen-agentchat/tests/test_messages.py:50L
17	3.8s	44,800	660	1	51c	text(58tok): Now I have enough understanding. Let me implement the fix. T
18	7.1s	45,460	2,520	0	160c	think(117tok): Now I have all the information I need. Let me implement the fixes: 1. **`_event
19	5.2s	47,980	448	34	176c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py
20	4.5s	48,428	327	59	176c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py
21	3.3s	48,755	376	72	176c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_events.py
22	5.5s	49,131	306	65	160c	TodoWrite
23	4.6s	49,437	283	72	161c	Edit python/packages/autogen-agentchat/src/autogen_agentchat/base/_task.py
24	3.3s	49,720	395	60	160c	TodoWrite
25	7.6s	50,115	283	1	167c	text(29tok): Now fix `Response`. It's a `@dataclass` — `SerializeAsAny` d
26	4.5s	50,398	650	68	160c	TodoWrite
27	3.7s	51,048	283	2	1,059c	text(18tok): Now write the tests. Let me look at the existing test struct
28	3.8s	51,331	459	1	2,285c	text(15tok): Now I'll add the serialization tests to `test_messages.py`:
29	2.5s	51,790	883	62	112c	Bash: wc -l /tmp/ct-eval-autogen-serialization-data-loss-xZk4x5/python/packages/autoge
30	2.9s	52,673	155	72	761c	Read python/packages/autogen-agentchat/tests/test_messages.py@360:10L
SUM	150.4s	1,123,705	41,950	1,107	70,857c

autogen-provider-namespace-restriction

baseline — PASS — $0.65 — 450s

Metric	Tokens	Note
Cache read	1,020,004	0.1x cost weight
Cache create	58,367	1.25x cost weight
Output (total)	13,464	5x cost weight
Thinking	12,215	91% of output
Non-thinking	1,249	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$0.62	1,025,935	12,583	991,415	34,488
claude-haiku-4-5-20251001	$0.04	52,485	881	28,589	23,879

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,093	8	0c	think(17tok): Let me explore the codebase to find the relevant files for this task.
2	0.2s	0	13,809	5	257c	Grep 'class ComponentLoader' in /tmp/ct-eval-autogen-provider-namespace-restriction-uz3HvB
3	4.4s	13,809	971	1	31,486c	Read python/packages/autogen-core/src/autogen_core/_component_config.py
4	0.5s	16,306	560	51	12,018c	Read python/packages/autogen-core/src/autogen_core/_component_config.py@160:120L
5	0.4s	16,866	3,846	9	2,879c	think(40tok): Now I need to look at the beginning of the `_component_config.py` file to unders
6	0.4s	20,712	1,185	68	7,676c	Read python/packages/autogen-core/src/autogen_core/_component_config.py@50:110L
7	0.9s	20,712	3,605	10	2,806c	think(392tok): Now I have a good picture. Let me make the changes: 1. ComponentLoader: Add
8	8.0s	24,317	2,292	8	165c	think(127tok): Now I have a clear picture. Let me make the changes: 1. **`_component_config.py
9	6.0s	26,609	448	67	165c	Edit python/packages/autogen-core/src/autogen_core/_component_config.py
10	7.3s	27,057	459	8	171c	think(23tok): Those diagnostics are pre-existing and unrelated. Now let me update the VideoSur
11	28.2s	27,516	350	72	171c	Edit python/packages/autogen-ext/src/autogen_ext/agents/video_surfer/tools.py
12	26.4s	27,866	1,054	8	3,816c	think(135tok): The import warnings about `os`, `pathlib`, and `urllib.parse` not being accessed
13	5.7s	28,920	1,482	65	2,980c	Read python/packages/autogen-core/tests/test_component_config.py@219:80L
14	72.2s	30,402	1,104	10	698c	think(1562tok): Now I see the end of the test file is at line 297. I need to add tests for the n
15	4.8s	31,506	4,333	46	165c	Edit python/packages/autogen-core/src/autogen_core/_component_config.py
16	7.2s	35,839	226	70	165c	Edit python/packages/autogen-core/src/autogen_core/_component_config.py
17	6.0s	36,065	612	8	491c	think(48tok): The "sys is not accessed" is a false positive from Pyright - it IS used in `sys.
18	4.7s	36,677	368	65	1,617c	Read python/packages/autogen-core/tests/test_component_config.py@299:30L
19	4.5s	36,677	973	70	1,206c	Read python/packages/autogen-core/tests/test_component_config.py@329:20L
20	5.8s	37,650	488	70	1,488c	Read python/packages/autogen-core/tests/test_component_config.py@348:30L
21	16.5s	38,138	563	1	158c	text(16tok): Good, line 370 is the end. Now let me append the security te
22	6.3s	38,701	1,062	2	315c	text(11tok): Now create the VideoSurfer tools test file:
23	7.0s	39,763	808	64	44c	Bash: ls /tmp/ct-eval-autogen-provider-namespace-restriction-uz3HvB/python/packages/au
24	24.3s	40,571	134	45	156c	Write python/packages/autogen-ext/tests/agents/test_video_surfer_tools.py
25	7.4s	40,705	793	4	1,069c	text(16tok): Now let's run the new component config tests to verify they
26	11.3s	41,498	885	63	31c	Bash: pip show autogen-test-utils 2>/dev/null \| head -5; find /tmp/ct-eval-autogen-pro
27	5.7s	42,383	158	60	1,069c	Bash: find /tmp/ct-eval-autogen-provider-namespace-restriction-uz3HvB -name "conftest.
28	5.6s	42,541	548	62	1,030c	Bash: pip install -e ../autogen-test-utils -q && python -m pytest tests/test_component
29	35.0s	43,089	432	50	102c	Bash: find / -name "pytest.ini" -o -name "pyproject.toml" 2>/dev/null \| grep autogen-c
30	18.8s	43,521	153	60	287c	Bash: grep -A 10 "\[tool.pytest" /tmp/ct-eval-autogen-provider-namespace-restriction-u
31	5.3s	43,674	247	53	36c	Bash: which uv && uv --version 2>/dev/null \| head -2
32	43.4s	43,921	227	66	1,952c	Bash: uv run pytest tests/test_component_config.py -x -q --tb=short 2>&1 \| tail -50
SUM	380.0s	1,005,224	49,268	1,249	76,669c

llamaindex-async-postprocess

baseline — FAIL — $0.76 — 252s

Metric	Tokens	Note
Cache read	1,358,990	0.1x cost weight
Cache create	82,458	1.25x cost weight
Output (total)	17,046	5x cost weight
Thinking	16,042	94% of output
Non-thinking	1,004	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$0.65	1,092,987	12,287	1,051,979	40,976
claude-haiku-4-5-20251001	$0.11	348,544	4,759	307,011	41,482

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,133	8	0c	think(22tok): Let me explore the codebase to understand the structure and find the affected co
2	3.4s	12,608	1,340	3	2,010c	Bash: find /tmp/ct-eval-llamaindex-async-postprocess-t9cD05 -type f -name "*.py" \| hea
3	0.0s	13,948	1,499	1	10,655c	Grep 'apostprocess_nodes\|postprocess_nodes' in .
4	0.6s	15,447	4,200	3	3,508c	Read llama-index-core/llama_index/core/postprocessor/types.py
5	0.4s	19,647	1,362	1	27,194c	Read llama-index-core/llama_index/core/tools/retriever_tool.py
6	0.1s	21,009	8,739	1	53,164c	Read llama-index-core/llama_index/core/chat_engine/context.py
7	0.3s	29,748	15,965	1	8,774c	Read llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/query.py:100L
8	3.9s	45,713	3,001	3	1,647c	Grep 'async def.\n.postprocess_nodes\(' in llama-index-core/llama_index/core/tools/retriever_tool.py
9	4.5s	48,714	725	1	2,465c	Bash: grep -n "async def.aretrieve\\|async def.achat\\|async def.*astream_chat\\|async
10	16.7s	49,439	1,299	1	18,765c	Read llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/query.py
11	0.7s	16,346	2,958	8	7,580c	think(96tok): Now I have a clear picture of all the bugs. Let me read each affected file and f
12	0.9s	19,304	3,010	8	2,777c	think(16tok): Now let me also read the integration files (vectara and lancedb):
13	10.6s	22,314	1,171	8	145c	think(276tok): Now I have a clear picture of all the bugs. Let me fix them all: 1. **context.p
14	4.8s	23,485	931	67	159c	Edit llama-index-core/llama_index/core/chat_engine/condense_plus_context.py
15	8.8s	24,416	474	8	157c	think(56tok): Now let me fix the multi_modal_context.py (chat engine), multi_modal.py (query e
16	6.0s	24,890	929	69	150c	Edit llama-index-core/llama_index/core/query_engine/multi_modal.py
17	6.5s	25,819	877	72	146c	Edit llama-index-core/llama_index/core/tools/retriever_tool.py
18	5.5s	26,696	754	1	146c	text(19tok): Now add the `_async_apply_node_postprocessors` method to `re
19	8.7s	27,450	667	9	2,352c	think(204tok): The error says it can't find `_async_apply_node_postprocessors` at line 113, but
20	11.8s	28,117	1,083	8	202c	think(50tok): The code looks correct. The Pyright error is likely a false positive or a resolu
21	4.2s	29,200	969	1	6,898c	text(54tok): Now fix lancedb. Since `LanceDBRetrieverQueryEngine` inherit
22	8.1s	30,169	2,756	1	209c	text(41tok): `LanceDBRetrieverQueryEngine` inherits from `RetrieverQueryE
23	1.2s	32,925	443	4	3,138c	text(19tok): Now let me write the tests. First, let me check what test st
24	0.8s	33,368	1,862	58	3,247c	Read llama-index-core/tests/chat_engine/test_context.py:60L
25	0.4s	35,230	1,600	62	5,614c	Read llama-index-core/tests/tools/test_retriever_tool.py
26	5.5s	36,830	2,044	8	3,404c	think(133tok): The existing test for `test_retriever_tool_async` already tests async with the s
27	0.0s	38,874	1,278	8	11,571c	think(193tok): Now I understand the structure clearly. The default implementation of `_apostpro
28	9.9s	40,152	4,412	2	139c	text(27tok): Now I'll write the tests. I'll add async postprocessor tests
29	6.9s	44,564	516	73	139c	Edit llama-index-core/tests/chat_engine/test_context.py
30	9.4s	45,080	584	8	769c	think(43tok): The Pyright diagnostics say these imports are not accessed yet. That's because t
31	2.7s	45,664	1,320	59	1,110c	Read llama-index-core/tests/chat_engine/test_context.py@210:20L
32	2.5s	46,984	579	65	694c	Read llama-index-core/tests/chat_engine/test_context.py@229:20L
33	5.1s	46,984	922	46	139c	Edit llama-index-core/tests/chat_engine/test_context.py
34	5.3s	47,906	504	1	843c	text(15tok): Now add a similar test to `test_condense_plus_context.py`:
35	3.6s	48,410	422	72	2,330c	Read llama-index-core/tests/chat_engine/test_condense_plus_context.py@80:50L
36	3.4s	48,832	899	65	961c	Read llama-index-core/tests/chat_engine/test_condense_plus_context.py@129:30L
37	8.3s	49,731	434	46	153c	Edit llama-index-core/tests/chat_engine/test_condense_plus_context.py
38	6.5s	50,165	696	72	477c	Edit llama-index-core/tests/chat_engine/test_condense_plus_context.py
39	6.2s	50,861	749	72	153c	Edit llama-index-core/tests/chat_engine/test_condense_plus_context.py
SUM	184.0s	1,308,252	79,106	1,004	183,984c

cli-v0.0.3 — PASS — $0.76 — 216s

Metric	Tokens	Note
Cache read	1,149,085	0.1x cost weight
Cache create	105,407	1.25x cost weight
Output (total)	15,954	5x cost weight
Thinking	15,188	95% of output
Non-thinking	766	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$0.65	820,664	10,724	749,590	71,047
claude-haiku-4-5-20251001	$0.11	433,932	5,230	399,495	34,360

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,237	8	2,259c	think(19tok): Let me start by reading the root NODE.md to understand the project structure.
2	2.1s	16,450	780	69	4,766c	Read core/NODE.md
3	8.5s	16,450	2,251	8	0c	think(36tok): Let me look at the postprocessors module and find the async methods, then search
4	1.5s	12,608	1,417	7	58c	Glob '*/postprocess.py'
5	1.1s	14,025	702	1	1,711c	Read llama-index-core/llama_index/core/indices/postprocessor.py
6	1.1s	14,025	1,423	4	56c	Glob '**/postprocessor/types.py'
7	0.9s	14,727	865	72	3,404c	Read llama-index-core/llama_index/core/postprocessor/types.py
8	0.4s	15,592	1,140	1	7,776c	Grep 'async def' in /tmp/ct-eval-llamaindex-async-postprocess-oyP8zF
9	0.4s	16,732	3,636	1	12,129c	Grep '\.postprocess_nodes\(' in /tmp/ct-eval-llamaindex-async-postprocess-oyP8zF
10	0.4s	20,368	5,061	1	7,125c	Read llama-index-core/llama_index/core/chat_engine/condense_plus_context.py@200:50L
11	0.6s	25,429	2,457	1	9,185c	Read llama-index-core/llama_index/core/query_engine/citation_query_engine.py@230:60L
12	0.4s	27,886	3,213	1	5,580c	Read llama-index-core/llama_index/core/query_engine/multi_modal.py@85:100L
13	0.3s	31,099	2,058	1	22,976c	Grep '_apply_node_postprocessors\|_aget_nodes' in /tmp/ct-eval-llamaindex-async-postprocess-oyP8zF
14	2.3s	33,157	9,020	1	1,418c	Bash: find . -path "query_engine.py" -type f \| head -20
15	2.0s	42,177	645	3	2,367c	Grep '\.postprocess_nodes\(' in /tmp/ct-eval-llamaindex-async-postprocess-oyP8zF
16	2.0s	42,822	1,123	1	2,076c	Grep '\.apostprocess_nodes\(' in /tmp/ct-eval-llamaindex-async-postprocess-oyP8zF
17	11.1s	43,945	958	4	6,113c	Read llama-index-core/llama_index/core/chat_engine/condense_plus_context.py@1:30L
18	0.6s	18,701	1,920	8	8,954c	think(159tok): Now I have a clear picture of the bugs. Let me read the specific files to unders
19	0.6s	20,621	3,798	8	3,773c	think(30tok): Now let me also check the retriever_tool.py to see if there's an async call path
20	3.1s	24,419	1,458	8	2,602c	think(17tok): Now let me check the retriever_tool.py for its async call (`acall`):
21	0.2s	25,877	974	8	28c	think(39tok): Now I have a clear picture. Let me also check the retriever_query_engine.py to c
22	2.4s	26,851	315	63	5,732c	Glob 'llama-index-core/tests/*/.py'
23	3.1s	26,851	2,451	34	5,825c	Read llama-index-core/tests/chat_engine/test_condense_plus_context.py
24	10.2s	29,302	2,177	9	159c	think(230tok): Now I have enough context to make all the fixes. Let me plan the changes: 1. **
25	3.8s	31,479	750	67	145c	Edit llama-index-core/llama_index/core/chat_engine/context.py
26	3.7s	32,229	469	72	171c	Edit llama-index-core/llama_index/core/chat_engine/multi_modal_condense_plus_context.py
27	4.7s	32,698	482	72	160c	Edit llama-index-core/llama_index/core/query_engine/citation_query_engine.py
28	7.5s	33,180	513	1	157c	text(26tok): Now fix the helper-method pattern in `multi_modal_context.py
29	6.5s	33,693	789	72	150c	Edit llama-index-core/llama_index/core/query_engine/multi_modal.py
30	9.0s	34,482	882	73	146c	Edit llama-index-core/llama_index/core/tools/retriever_tool.py
31	5.0s	35,364	766	1	146c	text(19tok): Now add the `_async_apply_node_postprocessors` method to `re
32	3.3s	36,130	771	10	2,352c	think(30tok): It seems the `_async_apply_node_postprocessors` is added after the `acall` metho
33	0.8s	36,901	905	8	9,643c	think(125tok): The Pyright diagnostic about `_async_apply_node_postprocessors` being unknown is
34	0.3s	37,806	3,691	9	550c	think(26tok): Now let me look at existing query engine tests and retriever tool tests to under
35	0.7s	41,497	496	46	5,614c	Read llama-index-core/tests/tools/test_retriever_tool.py
36	32.2s	41,993	2,163	8	130c	think(398tok): I see that there are already some test files for async retriever tool and retrie
37	8.7s	11,213	35,447	3	1,226c	text(11tok): Now let's run the tests to verify they pass:
38	8.7s	46,660	870	1	1,697c	text(31tok): All 6 tests pass. Let me also quickly run the existing chat
39	—	47,530	692	1	0c	text(348tok): All 35 existing tests still pass (the warnings are pre-exist
SUM	150.2s	1,104,182	104,765	766	138,359c

llamaindex-run-id-passthrough

baseline — FAIL — $0.84 — 234s

Metric	Tokens	Note
Cache read	1,960,130	0.1x cost weight
Cache create	106,834	1.25x cost weight
Output (total)	15,653	5x cost weight
Thinking	14,769	94% of output
Non-thinking	884	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$0.65	1,108,389	10,836	1,063,016	44,711
claude-haiku-4-5-20251001	$0.19	959,303	4,817	897,114	62,123

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	5,121	8	0c	think(29tok): Let me explore the codebase to understand the agent workflow structure and find
2	2.2s	0	13,900	3	2,386c	Bash: find /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF -type d -name "agent" \|
3	1.5s	13,900	1,664	1	325c	Bash: ls -la /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-core/llama_
4	1.4s	15,564	318	1	667c	Bash: ls -la /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-core/llama_
5	0.3s	15,882	516	1	1,794c	Grep 'run_id' in llama-index-core/llama_index/core/agent
6	0.0s	16,398	1,051	2	70,080c	Read llama-index-core/llama_index/core/agent/workflow/agent_context.py
7	2.1s	17,449	21,104	1	5,203c	Read llama-index-core/llama_index/core/agent/workflow/workflow_events.py
8	2.1s	38,553	1,709	1	31c	Bash: grep -r "class Context" /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-
9	2.0s	40,262	142	3	1,472c	Bash: find /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-core/llama_in
10	1.3s	40,262	892	6	390c	Read llama-index-core/llama_index/core/workflow/context.py:100L
11	1.5s	40,404	985	1	77c	Grep 'run_id' in llama-index-core
12	0.5s	41,389	289	3	2,005c	Read llama-index-core/llama_index/core/langchain_helpers/streaming.py:50L
13	0.3s	41,678	938	4	9,079c	Read llama-index-core/llama_index/core/agent/workflow/react_agent.py:100L
14	2.1s	42,616	3,023	1	1,085c	Bash: find /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-core/tests/ag
15	1.4s	42,616	3,609	1	3,063c	Read llama-index-core/tests/agent/workflow/test_single_agent_workflow.py:80L
16	2.2s	46,225	1,165	3	31c	Bash: grep -r "run_id" /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-c
17	1.8s	47,390	139	3	4,893c	Read llama-index-core/llama_index/core/agent/workflow/codeact_agent.py:100L
18	2.2s	47,529	1,578	2	31c	Bash: find /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF -path "*/.venv" -prune -o
19	1.4s	49,107	146	1	406c	Read llama-index-core/llama_index/core/workflow/workflow.py:150L
20	1.8s	49,253	244	1	595c	Bash: find /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF -name "README*" -o -name
21	1.7s	49,497	493	1	57c	Bash: git log --all --oneline --grep="run_id" 2>/dev/null \| head -10
22	1.9s	49,990	126	4	1,230c	Bash: git show c779a083f --stat 2>/dev/null \| head -50
23	1.4s	49,990	590	1	1,727c	Bash: git log --all --oneline \| grep -i "run\\|agent\\|passthrough" \| head -20
24	13.0s	50,580	659	1	22,618c	Bash: git show dee5e09b5 2>/dev/null
25	0.5s	16,334	1,856	8	9,912c	think(41tok): The explore agent gave a good overview but I need to see the actual code to unde
26	0.6s	18,190	3,706	8	6,389c	think(30tok): Now let me look at the `run()` method of `BaseWorkflowAgent` and `AgentWorkflow`
27	0.4s	21,896	2,815	8	5,616c	think(27tok): No `run_id` references in the agent workflow directory. Let me look at the full
28	0.8s	24,711	1,937	8	150c	think(17tok): Now let me check how the parent `Workflow.run()` handles `run_id`.
29	0.4s	26,648	498	69	1,976c	Grep 'run_id' in llama-index-core/llama_index/core/workflow
30	1.5s	27,146	906	8	85c	think(41tok): The parent `Workflow.run()` is in the `workflows` package (not in this repo, it'
31	2.0s	28,052	382	65	406c	Read llama-index-core/llama_index/core/workflow/workflow.py
32	8.9s	28,052	591	50	407c	Bash: find / -path "*/workflows/workflow.py" 2>/dev/null \| head -5
33	2.4s	28,643	271	56	3,633c	Grep 'def run' in llama-index-core/.venv/lib/python3.12/site-packages/workflows/workflow.py
34	2.2s	28,914	1,146	65	2,803c	Read llama-index-core/.venv/lib/python3.12/site-packages/workflows/workflow.py@408:60L
35	2.2s	28,914	1,996	72	2,098c	Read llama-index-core/.venv/lib/python3.12/site-packages/workflows/workflow.py@466:40L
36	12.7s	30,910	718	13	443c	think(280tok): Now I understand the issue. The parent `Workflow.run()` does: 1. `run_id = kwarg
37	0.1s	31,628	1,009	1	19,432c	text(108tok): Now I have a complete picture. The issue is clear: In both
38	5.2s	32,637	5,490	8	742c	think(30tok): Now I have a clear picture. Let me check how `WorkflowHandler` exposes the `run_
39	13.9s	38,127	1,133	8	152c	think(212tok): Good. The `WorkflowHandler` has `run_id` as an attribute (set from `external_ada
40	6.3s	39,260	1,160	67	162c	Edit llama-index-core/llama_index/core/agent/workflow/multi_agent_workflow.py
41	0.9s	40,420	1,188	8	2,045c	think(219tok): The diagnostics are pre-existing issues not related to my changes. Now let me al
42	19.7s	41,608	2,018	8	325c	think(427tok): Good, the diagnostics are pre-existing issues (the pyright can't resolve the `wo
43	3.5s	43,626	1,192	66	760c	Bash: sed -n '185,210p' /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-
44	0.7s	44,818	344	8	1,560c	think(155tok): `run_id` is not a property on `Context` itself - it's managed through the `Exter
45	2.6s	45,162	932	62	120c	Bash: wc -l /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-core/tests/a
46	2.4s	45,162	1,118	69	934c	Read llama-index-core/tests/agent/workflow/test_multi_agent_workflow.py@680
47	6.0s	46,280	388	2	157c	text(12tok): Now I'll add the run_id tests to both test files:
48	2.4s	46,668	646	2	884c	text(15tok): Now append the run_id tests to the single-agent test file:
49	8.2s	47,314	1,568	8	157c	think(20tok): The pyright diagnostics are all pre-existing issues. Now let me append the tests
50	5.2s	48,882	558	1	156c	text(11tok): Now add tests to the multi-agent test file:
51	3.6s	49,440	993	8	157c	think(17tok): I imported `Context` but didn't use it. Let me remove that import.
52	4.5s	50,433	1,495	1	235c	text(22tok): All remaining diagnostics are pre-existing. Now let me run t
53	6.3s	51,928	1,536	73	3,460c	Bash: cd /tmp/ct-eval-llamaindex-run-id-passthrough-C0gtqF/llama-index-core && .venv/b
SUM	172.3s	1,909,550	99,991	884	194,601c

vercel-ai-oauth-trailing-slash

baseline — PASS — $0.71 — 200s

Metric	Tokens	Note
Cache read	1,264,399	0.1x cost weight
Cache create	47,753	1.25x cost weight
Output (total)	9,889	5x cost weight
Thinking	8,988	91% of output
Non-thinking	901	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	8,668	8	1,360c	think(16tok): Let me find where the MCP OAuth flow processes the resource URL.
2	0.7s	19,881	704	51	37,683c	Read packages/mcp/src/util/oauth-util.ts
3	12.1s	20,585	12,225	8	5,679c	think(299tok): I can see the issue. In `resourceUrlFromServerUrl` in `oauth-util.ts`, it return
4	23.4s	32,810	2,410	8	3,458c	think(445tok): Now I understand the issue. The `resource.href` for `new URL("https://mcp.exampl
5	3.9s	35,220	2,614	32	143c	Grep 'resource\.href' in .
6	11.8s	37,834	184	8	126c	think(103tok): Now I have a clear picture. The issue is that `resource.href` in three places in
7	4.5s	38,018	705	1	121c	text(14tok): Now update `oauth.ts` to import and use the new helper:
8	6.9s	38,723	275	2	121c	text(11tok): Now replace the three `resource.href` calls:
9	6.8s	38,998	295	72	121c	Edit packages/mcp/src/tool/oauth.ts
10	4.7s	39,293	417	73	121c	Edit packages/mcp/src/tool/oauth.ts
11	10.4s	39,710	385	2	131c	text(16tok): Now add tests for `resourceHrefFromUrl` in `oauth.util.test.
12	7.0s	40,095	279	72	131c	Edit packages/mcp/src/util/oauth.util.test.ts
13	5.9s	40,374	525	2	4,309c	text(54tok): Now add tests to `oauth.test.ts` verifying the resource para
14	2.9s	40,899	1,691	67	2,615c	Read packages/mcp/src/tool/oauth.test.ts@826:65L
15	2.9s	42,590	918	72	2,257c	Read packages/mcp/src/tool/oauth.test.ts@1055:50L
16	2.9s	43,508	921	72	1,346c	Read packages/mcp/src/tool/oauth.test.ts@1270:30L
17	3.5s	44,429	577	1	2,258c	text(42tok): Now I'll add the trailing slash tests to `oauth.test.ts`. Le
18	6.2s	45,006	893	46	126c	Edit packages/mcp/src/tool/oauth.test.ts
19	3.3s	45,899	566	2	1,428c	text(26tok): Now add similar tests to `exchangeAuthorization` and `refres
20	8.8s	46,465	653	72	126c	Edit packages/mcp/src/tool/oauth.test.ts
21	5.0s	47,118	731	2	2,256c	text(31tok): Now find a good spot in `refreshAuthorization` tests to add
22	3.6s	47,849	1,016	1	2,035c	text(23tok): I need to find a test in `refreshAuthorization` that uses `v
23	8.6s	48,865	872	54	126c	Edit packages/mcp/src/tool/oauth.test.ts
24	4.4s	49,737	913	6	5,087c	text(9tok): Now let's run the tests to verify:
25	5.8s	50,650	2,830	9	3,250c	think(89tok): The test failures are unrelated to my changes - they're pre-existing failures du
26	6.3s	53,480	1,937	8	291c	think(71tok): The `oauth.util.test.ts` (13 tests, all passing) passed but `oauth.test.ts` fail
27	7.6s	55,417	386	63	1,834c	Bash: cd /tmp/ct-eval-vercel-ai-oauth-trailing-slash-AzFojv/packages/mcp && pnpm vites
28	5.7s	55,803	1,162	1	1,416c	text(45tok): There's an existing test at line 1911 that expected `'https:
29	3.0s	56,965	595	73	2,305c	Read packages/mcp/src/tool/oauth.test.ts@1850:45L
30	12.5s	56,965	1,406	13	126c	think(198tok): I see the issue. The PRM resource is `'https://api.example.com/'` - this is a UR
SUM	191.4s	1,264,399	47,753	901	82,386c

cli-v0.0.3 — PASS — $0.75 — 216s

Metric	Tokens	Note
Cache read	1,302,023	0.1x cost weight
Cache create	51,885	1.25x cost weight
Output (total)	10,771	5x cost weight
Thinking	9,891	92% of output
Non-thinking	880	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	8,811	8	2,191c	think(34tok): Let me start by reading the root NODE.md to understand the project structure, th
2	3.6s	20,024	754	35	643c	Grep 'oauth\|OAuth\|resource.param\|mcp.oauth' in packages
3	0.4s	20,778	433	69	37,683c	Read packages/mcp/src/tool/oauth.ts
4	0.7s	21,211	11,351	8	9,137c	think(371tok): Now I can see the issue. In `oauth.ts`, there are three places where `resource.h
5	7.1s	32,562	4,891	12	1,523c	think(131tok): Now I have a clear picture. The fix should be: 1. Add a `resourceHref` helper f
6	5.5s	37,453	773	59	7,425c	Read packages/mcp/src/tool/oauth.test.ts@729:200L
7	22.7s	38,226	2,521	8	100c	think(342tok): Now I have a clear understanding of the issue and the codebase. Here's my plan:
8	7.2s	40,747	1,593	59	126c	Edit packages/mcp/src/util/oauth-util.ts
9	4.2s	42,340	550	2	121c	text(14tok): Now update `oauth.ts` to import and use `resourceHref`:
10	4.6s	42,890	274	1	152c	text(11tok): Now replace the three `resource.href` usages:
11	6.1s	43,164	241	71	121c	Edit packages/mcp/src/tool/oauth.ts
12	4.4s	43,405	253	1	209c	text(23tok): Wait, let me verify the current state of those lines to make
13	7.5s	43,658	242	1	131c	text(10tok): All 3 usages are fixed. Now add tests:
14	8.9s	43,900	373	72	131c	Edit packages/mcp/src/util/oauth.util.test.ts
15	5.8s	44,273	688	2	1,523c	text(21tok): Now add tests to `oauth.test.ts` for the three functions wit
16	3.2s	44,961	630	62	648c	Read packages/mcp/src/tool/oauth.test.ts@880:10L
17	7.1s	44,961	942	65	126c	Edit packages/mcp/src/tool/oauth.test.ts
18	4.2s	45,903	777	3	5,070c	text(29tok): Now add similar tests to `exchangeAuthorization` and `refres
19	5.2s	46,680	1,873	73	2,638c	Read packages/mcp/src/tool/oauth.test.ts@1080:60L
20	7.2s	48,553	1,051	46	126c	Edit packages/mcp/src/tool/oauth.test.ts
21	3.3s	49,604	684	1	2,524c	text(19tok): Now find the end of `refreshAuthorization` tests to add simi
22	5.5s	50,288	1,106	65	1,266c	Read packages/mcp/src/tool/oauth.test.ts@1330:30L
23	7.4s	50,288	1,657	46	126c	Edit packages/mcp/src/tool/oauth.test.ts
24	4.8s	51,945	678	4	5,141c	text(13tok): Now let's run the tests to verify everything passes:
25	12.1s	52,623	2,849	9	3,250c	think(272tok): The failures are not related to my changes - they're pre-existing infrastructure
26	5.9s	55,472	2,327	8	291c	think(56tok): The `oauth.util.test.ts` passed (14 tests). The `oauth.test.ts` failed because i
27	3.4s	57,799	385	63	1,834c	Bash: cd /tmp/ct-eval-vercel-ai-oauth-trailing-slash-WFRoay/packages/mcp && pnpm vites
28	5.7s	57,799	1,444	8	1,679c	think(53tok): There's a pre-existing test that was expecting the old behavior with trailing sl
29	8.9s	59,243	817	11	2,206c	think(119tok): I need to look at the test context to understand what resource this is using. Th
30	15.9s	60,060	917	8	126c	think(404tok): I see. The PRM's resource is `'https://api.example.com/'` (with trailing slash,
SUM	188.2s	1,302,023	51,885	880	88,267c

vercel-ai-error-code

baseline — PASS — $1.96 — 739s

Metric	Tokens	Note
Cache read	5,381,292	0.1x cost weight
Cache create	178,243	1.25x cost weight
Output (total)	48,696	5x cost weight
Thinking	47,138	97% of output
Non-thinking	1,558	tool calls + text

Model Breakdown

Model	Cost	Input	Output	Cache Read	Cache Create
claude-sonnet-4-6	$1.44	2,276,396	30,646	2,190,624	85,730
claude-haiku-4-5-20251001	$0.53	3,283,260	18,050	3,190,668	92,513

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	8,425	8	0c	think(24tok): Let me explore the codebase to understand the structure and find the relevant co
2	2.0s	0	14,056	5	1,964c	Bash: find /tmp/ct-eval-vercel-ai-error-code-rxspi6 -type f -name ".ts" -o -name ".t
3	1.5s	14,056	1,834	1	1,589c	Bash: ls -la /tmp/ct-eval-vercel-ai-error-code-rxspi6/packages/ 2>/dev/null \| head -30
4	2.4s	15,890	1,077	1	2,893c	Bash: find /tmp/ct-eval-vercel-ai-error-code-rxspi6/packages -type f \( -name "*.ts" -
5	1.3s	16,967	1,365	54	3,604c	Bash: find /tmp/ct-eval-vercel-ai-error-code-rxspi6/packages/ai -type f \( -name "*.ts
6	1.7s	18,332	1,601	3	4,681c	Grep 'web_fetch_tool_result_error\|providerExec' in packages
7	2.0s	18,332	3,367	1	2,556c	Grep 'tool_result' in packages/anthropic/src
8	2.0s	21,699	1,099	1	204c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.ts
9	1.3s	22,798	165	33	8,740c	Grep 'tool_result\|errorCode' in packages/anthropic/src/convert-to-anthropic-messages-prompt.ts
10	2.0s	22,963	2,402	1	1,438c	Read packages/ai/src/generate-text/tool-result.ts
11	1.3s	25,365	607	1	7,576c	Read packages/ai/src/ui/convert-to-model-messages.ts:200L
12	1.7s	25,972	2,429	35	7,691c	Read packages/ai/src/ui/convert-to-model-messages.ts@200:200L
13	1.8s	28,401	2,117	1	188c	Bash: find /tmp/ct-eval-vercel-ai-error-code-rxspi6/packages -name "create-tool-model-
14	1.1s	30,518	296	51	1,371c	Read packages/ai/src/prompt/create-tool-model-output.ts
15	1.5s	30,814	568	4	5,499c	Bash: find /tmp/ct-eval-vercel-ai-error-code-rxspi6/packages/ai -name "stream" -type
16	1.6s	30,814	2,992	4	2,189c	Read packages/anthropic/src/__fixtures__/anthropic-web-fetch-tool.error.json
17	1.9s	33,806	908	1	301c	Bash: grep -n "web_fetch_tool_result_error" /tmp/ct-eval-vercel-ai-error-code-rxspi6/p
18	1.1s	34,714	244	45	5,679c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.test.ts@1400:150L
19	2.3s	34,958	2,019	1	10,513c	Read packages/ai/src/generate-text/run-tools-transformation.ts:300L
20	2.0s	36,977	3,640	3	5,764c	Read packages/ai/src/generate-text/run-tools-transformation.ts@300:400L
21	2.3s	40,617	1,675	1	6,483c	Grep 'tool-result\|errorText\|output' in packages/ai/src/ui/process-ui-message-stream.ts
22	2.1s	42,292	1,923	1	31c	Bash: grep -n "tool-error\\|tool-result" /tmp/ct-eval-vercel-ai-error-code-rxspi6/packa
23	1.3s	44,215	149	4	7,709c	Read packages/ai/src/ui/process-ui-message-stream.ts:200L
24	2.2s	44,364	2,484	1	12,646c	Read packages/ai/src/ui/process-ui-message-stream.ts@400:300L
25	1.9s	46,848	3,649	35	4,242c	Read packages/ai/src/ui/process-ui-message-stream.ts@698:100L
26	2.9s	50,497	1,273	1	81c	Bash: grep -n "getErrorMessage\\|JSON.stringify\\|errorText" /tmp/ct-eval-vercel-ai-erro
27	1.8s	51,770	166	1	345c	Grep 'tool-result\|isError' in packages/provider/src/language-model/v4
28	1.1s	51,936	288	45	3,636c	Read packages/provider/src/language-model/v4/language-model-v4-stream-part.ts
29	1.6s	52,224	1,406	35	1,839c	Read packages/provider/src/language-model/v4/language-model-v4-tool-result.ts
30	1.8s	53,630	697	1	956c	Bash: grep -n "tool-result\\|ToolResult" /tmp/ct-eval-vercel-ai-error-code-rxspi6/packa
31	2.4s	54,327	432	3	9,843c	Read packages/anthropic/src/anthropic-messages-language-model.ts@1540:200L
32	3.0s	54,327	3,334	1	2,179c	Read packages/ai/src/generate-text/run-tools-transformation.ts@373:50L
33	2.0s	57,661	816	1	31c	Bash: grep -n "getErrorMessage" /tmp/ct-eval-vercel-ai-error-code-rxspi6/packages/ai/s
34	1.6s	58,477	185	1	552c	Bash: grep -rn "tool-output-error\\|errorText" /tmp/ct-eval-vercel-ai-error-code-rxspi6
35	1.5s	58,662	351	1	4,178c	Read packages/ai/src/generate-text/stream-text.ts@2590:100L
36	2.0s	58,662	1,717	1	31c	Bash: grep -n "const onError\\|function onError" /tmp/ct-eval-vercel-ai-error-code-rxsp
37	1.2s	60,379	238	66	777c	Bash: grep -n "onError" /tmp/ct-eval-vercel-ai-error-code-rxspi6/packages/ai/src/gener
38	1.3s	60,617	354	51	2,185c	Read packages/ai/src/generate-text/stream-text.ts@2395:50L
39	2.3s	60,617	1,152	1	290c	Bash: grep -rn "export.*getErrorMessage\\|function getErrorMessage" /tmp/ct-eval-vercel
40	1.3s	61,769	278	53	652c	Read packages/provider/src/errors/get-error-message.ts
41	2.4s	62,047	299	5	5,015c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.ts@864:100L
42	3.1s	62,346	1,486	1	2,510c	Read packages/ai/src/ui/convert-to-model-messages.ts@202:50L
43	2.1s	63,832	880	1	154c	Read packages/ai/src/prompt/create-tool-model-output.ts
44	5.5s	64,712	344	1	5,217c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.ts@300:100L
45	5.4s	65,056	1,561	3	128c	Bash: grep -n "type ToolResultPart\\|interface ToolResultPart" /tmp/ct-eval-vercel-ai-e
46	1.6s	66,617	473	45	1,614c	Read packages/provider-utils/src/types/content-part.ts@140:50L
47	1.5s	67,090	628	72	2,295c	Read packages/provider-utils/src/types/content-part.ts@185:80L
48	8.5s	67,718	822	1	925c	Bash: grep -n "web_fetch_tool_result_error\\|errorText" /tmp/ct-eval-vercel-ai-error-co
49	1.6s	68,540	1,008	1	150c	Bash: grep -rn "tool-output-error\\|web_fetch_tool_result_error" /tmp/ct-eval-vercel-ai
50	1.5s	68,540	1,301	1	4,699c	Read packages/ai/src/generate-text/stream-text.test.ts@11500:100L
51	2.6s	69,548	1,646	2	935c	Bash: grep -B10 "type: 'tool-result'" /tmp/ct-eval-vercel-ai-error-code-rxspi6/package
52	1.7s	71,194	449	1	5,642c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.test.ts@1537:150L
53	3.7s	71,643	1,952	4	538c	Bash: grep -rn "unknown.errorCode\\|errorCode.unknown" /tmp/ct-eval-vercel-ai-error-c
54	2.5s	73,595	455	1	1,385c	Bash: grep -B5 -A30 "should preserve provider metadata when replaying" /tmp/ct-eval-ve
55	20.2s	74,050	608	1	889c	Bash: grep -rn "type JSONValue\\|export.*JSONValue" /tmp/ct-eval-vercel-ai-error-code-r
56	1.4s	74,658	2,485	61	769c	Read packages/provider/src/json-value/json-value.ts
57	26.4s	77,143	332	1	538c	Bash: grep -rn "??.*'unknown'\\|= 'unknown'" /tmp/ct-eval-vercel-ai-error-code-rxspi6/p
58	14.6s	77,475	3,211	1	1,058c	Bash: grep -rn "createToolModelOutput" /tmp/ct-eval-vercel-ai-error-code-rxspi6/packag
59	2.7s	80,686	1,842	5	5,016c	Read packages/ai/src/generate-text/to-response-messages.ts:150L
60	7.4s	82,528	1,779	1	31c	Bash: grep -n "providerExecuted.*true" /tmp/ct-eval-vercel-ai-error-code-rxspi6/packag
61	1.4s	84,307	731	1	31c	Bash: grep -n "web_fetch.*tool-result" /tmp/ct-eval-vercel-ai-error-code-rxspi6/packag
62	16.6s	85,038	129	3	13,521c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.test.ts@1390:200L
63	0.8s	19,638	2,261	8	1,858c	think(180tok): The exploration gave a good overview. Let me now look at specific files more car
64	0.6s	21,899	1,170	44	4,160c	Grep 'errorText\|tool-error\|isError' in packages/ai/src/generate-text/stream-text.ts
65	0.3s	23,069	1,454	8	4,700c	think(152tok): I can see something interesting. In `stream-text.ts` at line 1471, the `errorMod
66	0.8s	24,523	1,929	8	8,658c	think(348tok): Now let me trace the full pipeline for provider-executed tool errors: 1. In `ru
67	19.4s	26,452	2,949	8	5,263c	think(479tok): Now I see the issue more clearly. Let me trace the full pipeline: 1. When Anthr
68	8.8s	29,401	2,794	8	5,967c	think(164tok): Now I understand the full pipeline for `generateText`/`streamText` with multi-st
69	22.2s	32,195	2,087	8	2,641c	think(387tok): Now I have a clear picture. Let me trace the full pipeline: **Step 1: Anthropic
70	23.9s	34,282	1,807	8	3,442c	think(598tok): The issue is in `stream-text.ts` at line 1467-1471. This is for local (non-provi
71	2.5s	36,089	2,706	35	1,469c	Grep 'toResponseMessages\|stepToolOutputs.*tool' in packages/ai/src/generate-text/stream-text.ts
72	11.6s	38,795	576	8	1,268c	think(348tok): Now I have the picture. In `stream-text.ts` at line 2117-2123, `toResponseMessag
73	3.4s	39,371	1,131	8	795c	think(19tok): Now let me look at the `generateText` path to see if there's a difference.
74	7.3s	40,502	459	8	6,915c	think(102tok): OK so both `generateText` and `streamText` use `toResponseMessages` for the mult
75	28.7s	40,961	2,042	8	8,421c	think(588tok): Now I see the issue! Let me look at the `web_search` handling for error cases. A
76	18.6s	43,003	4,357	8	3,989c	think(466tok): I see that in `process-ui-message-stream.ts` line 707, the `errorText` is from `
77	4.3s	47,360	2,296	8	3,739c	think(134tok): Now I need to understand what Anthropic actually accepts as valid error codes. T
78	32.9s	49,656	1,358	8	2,155c	think(657tok): Now I see the bug for `web_search` and `tool_search`! When they return an error:
79	3.3s	51,014	2,929	51	2,137c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.test.ts@1537:50L
80	43.7s	53,943	808	8	374c	think(1410tok): Now I understand the existing test cases. There are 3 tests for the `web_fetch`
81	7.6s	54,751	2,984	51	2,111c	Read packages/ai/src/generate-text/stream-text.ts@2390:50L
82	12.2s	54,751	3,769	8	16c	think(295tok): Now I see - `toUIMessageStream` uses `onError = getErrorMessage` as default. So
83	3.4s	58,520	728	58	4,851c	Grep 'web_search_tool_result_error' in packages/anthropic/src
84	23.4s	59,248	1,762	8	105c	think(408tok): Now let me also look at the `run-tools-transformation.ts` to understand where `e
85	5.3s	61,010	1,233	45	1,326c	Read packages/ai/src/generate-text/tool-error.ts
86	26.5s	61,010	1,784	8	6,919c	think(548tok): OK, so `error: unknown`. The `error` field is `unknown` type, which means it cou
87	13.2s	62,794	3,966	8	3,426c	think(232tok): Now I see the important distinction. There are two paths in `convert-to-model-me
88	19.3s	66,760	1,631	8	2,826c	think(411tok): So `errorText` is always a `string` in the UI message. This confirms that the er
89	12.6s	68,391	1,816	8	4,789c	think(282tok): OK so the `web_search` error case is parsed correctly from the Anthropic API res
90	30.7s	70,207	1,884	8	16c	think(702tok): Now I understand the full picture. Let me also look at what happens when there's
91	4.8s	72,091	2,042	57	17,818c	Grep 'url_not_accessible\|url_not_allowed\|max_u' in packages/anthropic/src
92	33.2s	72,091	8,267	8	2,068c	think(599tok): Now I see some important info. The `code_execution` tool has valid error codes l
93	7.7s	80,358	2,865	8	3,260c	think(218tok): Now let me look at what `chunk.result` looks like in the streaming case. The chu
94	7.2s	83,223	1,411	8	16c	think(46tok): Now let me look at how `part.content.error_code` is parsed. Let me look at the s
95	5.6s	84,634	241	65	3,003c	Read packages/anthropic/src/anthropic-messages-language-model.ts@1490:60L
96	5.3s	84,634	1,298	8	16c	think(57tok): OK, let me look at the streaming message parsing schema. The `part` in the strea
97	3.6s	85,932	265	56	16c	Grep 'streamingMessageSchema\\|streaming_messag' in packages/anthropic/src/anthropic-messages-api.ts
98	4.1s	86,197	198	36	16c	Grep 'z\.discriminatedUnion.type.web_fetch\\|' in packages/anthropic/src/anthropic-messages-api.ts
99	3.1s	86,395	206	65	4,205c	Read packages/anthropic/src/anthropic-messages-api.ts@640:100L
100	27.2s	86,395	1,471	8	2,700c	think(464tok): I see the schema for `web_fetch_tool_result_error` uses `z.string()` for `error_
101	4.5s	87,866	2,371	8	16c	think(23tok): Let me look at what the Anthropic API schema for tool_search_tool_result expects
SUM	698.3s	5,296,254	175,504	1,558	313,656c

cli-v0.0.2 — PASS — $1.29 — 369s

Metric	Tokens	Note
Cache read	2,232,260	0.1x cost weight
Cache create	89,790	1.25x cost weight
Output (total)	19,063	5x cost weight
Thinking	18,100	95% of output
Non-thinking	963	tool calls + text

Turn-by-turn timeline

Note: "Out*" excludes thinking tokens (not reported per-turn by the API). "Time" is wall time between consecutive tool results (model generation + tool execution).

Turn	Time	Cache Rd	Cache Wr	Out*	Result	Actions
1	—	11,213	8,561	8	2,417c	think(26tok): Let me start by reading the root NODE.md to understand the project structure, th
2	2.7s	19,774	830	69	3,900c	Read providers/NODE.md
3	3.7s	20,604	1,481	8	2,113c	think(28tok): Let me look at the Anthropic provider implementation to understand how provider-
4	0.3s	22,085	864	59	408c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.ts
5	3.1s	22,949	306	34	9,967c	Grep 'provider_tool_result\|web_fetch_tool_resu' in packages/anthropic/src
6	16.6s	23,255	3,294	8	12,434c	think(64tok): Let me look at the convert-to-anthropic-messages-prompt.ts to understand how pro
7	9.6s	26,549	3,282	8	8,501c	think(245tok): Now I can see the issue. The `convert-to-anthropic-messages-prompt.ts` file hand
8	10.9s	29,831	2,989	8	11,862c	think(182tok): So the language model processes the `web_fetch_tool_result_error` and sets: ```j
9	0.6s	32,820	3,684	8	15,363c	think(159tok): So the streaming pipeline enqueues the tool result with: ```js { type: 'tool-r
10	0.1s	36,504	4,806	8	14,992c	think(50tok): Now I need to understand what `part.output` looks like. The `tool-result` part h
11	3.8s	41,310	5,057	32	1,371c	Read packages/ai/src/prompt/create-tool-model-output.ts
12	11.5s	41,310	5,625	10	5,263c	think(260tok): Now I'm understanding the flow. When a `web_fetch_tool_result_error` comes back
13	21.4s	46,935	2,301	8	1,531c	think(552tok): Now I understand the flow better. For a provider-executed tool-result (from Anth
14	2.5s	49,236	2,074	62	1,438c	Read packages/ai/src/generate-text/tool-result.ts
15	5.7s	49,236	2,658	8	16c	think(103tok): OK, so the `tool-result` ContentPart has `output` property. The provider-execute
16	3.7s	51,894	272	50	2,902c	Grep 'tool-result.output\|output.tool-result\|' in packages/ai/src/generate-text
17	17.0s	52,166	1,071	8	9,182c	think(311tok): Key finding: In `generate-text.ts` line 1517 and 1547: ```js output: part.result
18	13.7s	53,237	4,133	8	3,336c	think(340tok): Now I understand the tests. The existing tests are testing with `output.type ===
19	16.8s	57,370	1,718	8	2,845c	think(298tok): So now I see that when `part.isError` is true, the code creates a `tool-error` C
20	3.2s	59,088	1,990	69	4,497c	Read packages/ai/src/generate-text/stream-text.ts@2060:80L
21	4.6s	59,088	3,225	13	6,733c	think(84tok): Let me look at how `stepToolOutputs` is constructed and what the content passed
22	7.3s	62,313	1,893	8	342c	think(66tok): Let me look at how step content is being built - specifically how `tool-result`
23	2.9s	64,206	449	51	4,891c	Read packages/ai/src/generate-text/stream-text.ts@1820:100L
24	8.6s	64,206	1,829	8	3,078c	think(120tok): I see that in `stream-text.ts`, when a `tool-result` chunk arrives: - It pushes
25	5.4s	66,035	1,171	8	1,562c	think(83tok): Let me look at where the stream-text.ts builds the step content for `toResponseM
26	4.0s	67,206	742	66	3,287c	Read packages/ai/src/generate-text/stream-text.ts@998:80L
27	5.5s	67,948	1,116	8	5,805c	think(128tok): Now I see the flow more clearly. When a `tool-result` chunk with `isError: true`
28	39.5s	69,064	1,826	8	3,084c	think(889tok): Now I see the full picture! In `run-tools-transformation.ts` at line 376-388: `
29	6.3s	70,890	3,633	8	4,223c	think(63tok): This is for the local tool results (non-provider-executed). The provider-execute
30	6.9s	74,523	1,360	8	5,453c	think(211tok): In `generate-text.ts`, for the `toolOutputs` loop (line 591-607), when `output.t
31	4.3s	75,883	1,842	8	4,353c	think(56tok): I see. In `generate-text.ts`, only CLIENT tools (non-provider-executed) are run.
32	18.0s	77,725	1,534	8	2,039c	think(323tok): So I see clearly now. When `part.isError` is true (for `web_fetch_tool_result_er
33	18.0s	79,259	1,714	8	638c	think(457tok): This is getting complex. Let me look at whether the `tool-result` with `isError:
34	3.8s	80,973	1,243	46	652c	Read packages/provider/src/errors/get-error-message.ts
35	8.2s	80,973	1,542	8	2,736c	think(242tok): OK so `getErrorMessage({ type: 'web_fetch_tool_result_error', errorCode: 'url_no
36	22.1s	82,515	1,266	8	2,550c	think(441tok): OK this `toolOutputs` at line 562 is from `executeTools` for `localApprovedToolA
37	2.5s	83,781	1,852	69	2,236c	Read packages/anthropic/src/convert-to-anthropic-messages-prompt.ts@679:40L
38	26.0s	83,781	2,571	8	426c	think(620tok): OK wait, there's something important I'm noticing. At line 710: ```js if ( out
39	3.0s	86,352	1,821	71	113c	Grep 'toResponseMessages' in packages/ai/src/generate-text/generate-text.ts
40	2.3s	88,173	165	62	3,088c	Read packages/ai/src/generate-text/generate-text.ts@1040:60L
SUM	346.1s	2,232,260	89,790	963	171,627c

Summary

Case Details

nanobot-exectool-regex

baseline — PASS — $0.14 — 50s

cli-v0.0.2 — PASS — $0.20 — 70s

nanobot-streaming-metadata

baseline — PASS — $0.44 — 158s

Model Breakdown

cli-v0.0.3 — PASS — $0.37 — 92s

pydantic-importstring-error

baseline — PASS — $0.39 — 163s

cli-v0.0.2 — PASS — $0.39 — 180s

fastapi-optional-file-list

baseline — PASS — $0.50 — 183s

Model Breakdown

cli-v0.0.2 — PASS — $0.47 — 104s

langchain-merge-parallel-tools

baseline — PASS — $0.55 — 237s

cli-v0.0.2 — PASS — $0.50 — 187s

autogen-serialization-data-loss

baseline — PASS — $0.71 — 295s

Model Breakdown

cli-v0.0.3 — PASS — $0.66 — 199s

autogen-provider-namespace-restriction

baseline — PASS — $0.65 — 450s

Model Breakdown

llamaindex-async-postprocess

baseline — FAIL — $0.76 — 252s

Model Breakdown

cli-v0.0.3 — PASS — $0.76 — 216s

Model Breakdown

llamaindex-run-id-passthrough

baseline — FAIL — $0.84 — 234s

Model Breakdown

vercel-ai-oauth-trailing-slash

baseline — PASS — $0.71 — 200s

cli-v0.0.3 — PASS — $0.75 — 216s

vercel-ai-error-code

baseline — PASS — $1.96 — 739s

Model Breakdown

cli-v0.0.2 — PASS — $1.29 — 369s