mas_name stringclasses 7
values | llm_name stringclasses 5
values | benchmark_name stringclasses 8
values | trace_id int64 0 205 | trace dict | mast_annotation dict |
|---|---|---|---|---|---|
ChatDev | GPT-4o | ProgramDev | 0 | {"key":"ChatDev_ProgramDev_GPT4o","index":0,"trajectory":"[2025-31-03 19:09:41 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":0,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 1 | {"key":"ChatDev_ProgramDev_GPT4o","index":1,"trajectory":"[2025-31-03 19:30:18 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":0,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 2 | {"key":"ChatDev_ProgramDev_GPT4o","index":2,"trajectory":"[2025-31-03 19:48:48 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":0,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 3 | {"key":"ChatDev_ProgramDev_GPT4o","index":3,"trajectory":"[2025-31-03 20:04:23 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":0,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":1,"2.3":1,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 4 | {"key":"ChatDev_ProgramDev_GPT4o","index":4,"trajectory":"[2025-31-03 20:15:44 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":0,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 5 | {"key":"ChatDev_ProgramDev_GPT4o","index":5,"trajectory":"[2025-31-03 20:40:53 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":1,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":1,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 6 | {"key":"ChatDev_ProgramDev_GPT4o","index":6,"trajectory":"[2025-31-03 20:46:17 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":1,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 7 | {"key":"ChatDev_ProgramDev_GPT4o","index":7,"trajectory":"[2025-31-03 20:55:23 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":0,"1.2":0,"1.3":1,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 8 | {"key":"ChatDev_ProgramDev_GPT4o","index":8,"trajectory":"[2025-31-03 21:05:25 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":1,"1.2":0,"1.3":1,"1.4":0,"1.5":1,"2.1":0,"2.2":1,"2.3":1,"2.4":1,"2.5":1,"2.6":1,"3.1":1,"3.(...TRUNCATED) |
ChatDev | GPT-4o | ProgramDev | 9 | {"key":"ChatDev_ProgramDev_GPT4o","index":9,"trajectory":"[2025-31-03 21:19:38 INFO] **[Preprocessin(...TRUNCATED) | {"1.1":0,"1.2":0,"1.3":0,"1.4":0,"1.5":0,"2.1":0,"2.2":0,"2.3":0,"2.4":0,"2.5":0,"2.6":0,"3.1":0,"3.(...TRUNCATED) |
MAD: Multi-Agent System Traces Dataset
Execution traces from multi-agent systems (MAS), annotated with the Multi-Agent Systems Failure Taxonomy (MAST). Each record gives the MAS, the LLM behind it, the benchmark task, the full trace, and binary annotations for the 14 MAST failure modes.
Code: https://github.com/multi-agent-systems-failure-taxonomy/MAST
1642 traces · 7 MAS frameworks · 8 benchmarks · 5 LLMs.
Files
| file | rows | |
|---|---|---|
MAD_full_dataset.json |
1642 | traces with MAST annotations |
MAD_human_labelled_dataset.json |
19 | inter-annotator agreement study, 3 annotators |
Schema
| field | type | |
|---|---|---|
mas_name |
string | AG2, MetaGPT, ChatDev, Magentic, AppWorld, HyperAgent, OpenManus |
llm_name |
string | GPT-4o, Claude, GPT-4o-mini, Qwen, CodeLlama |
benchmark_name |
string | ProgramDev, ProgramDev-v2, GSM, Olympiad, GAIA, MMLU, Test-C, SWE-Bench-Lite |
trace_id |
int | index within its config |
trace |
dict | {key, index, trajectory} |
mast_annotation |
dict | 14 codes → 1, 0, or null where the annotation is unavailable |
Taxonomy
Specification — 1.1 Disobey Task Specification · 1.2 Disobey Role Specification ·
1.3 Step Repetition · 1.4 Loss of Conversation History · 1.5 Unaware of Termination Conditions
Inter-Agent Misalignment — 2.1 Conversation Reset · 2.2 Fail to Ask for Clarification ·
2.3 Task Derailment · 2.4 Information Withholding · 2.5 Ignored Other Agent's Input ·
2.6 Reasoning-Action Mismatch
Task Verification — 3.1 Premature Termination · 3.2 No or Incomplete Verification ·
3.3 Incorrect Verification
Notes
Annotations are produced by an LLM judge, not by human labelling.
In MAD_human_labelled_dataset.json, each round uses a different revision of the taxonomy
(18, 17, 17 and 14 modes) and the codes are not comparable across rounds.
Citation
@inproceedings{cemri2025mast,
title = {Why Do Multi-Agent LLM Systems Fail?},
author = {Cemri, Mert and Pan, Melissa Z. and Yang, Shuyi and Agrawal, Lakshya A. and Chopra, Bhavya and Tiwari, Rishabh and Keutzer, Kurt and Parameswaran, Aditya and Klein, Dan and Ramchandran, Kannan and Zaharia, Matei and Gonzalez, Joseph E. and Stoica, Ion},
booktitle = {Advances in Neural Information Processing Systems},
year = {2025}
}
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