@context dict | @type string | name string | description string | conformsTo string | url string | license string | version string | datePublished timestamp[s] | creator dict | keywords list | isLiveDataset bool | distribution list | recordSet list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
"@language": "en",
"@vocab": "https://schema.org/",
"citeAs": "cr:citeAs",
"column": "cr:column",
"conformsTo": "dct:conformsTo",
"cr": "http://mlcommons.org/croissant/",
"data": {
"@id": "cr:data",
"@type": "@json"
},
"dataBiases": "cr:dataBiases",
"dataCollection": "cr:dataCollection",
... | sc:Dataset | AgentDisruptBench | An evaluation methodology for evaluating AI agent resilience under runtime tool-call disruptions, designed for the NeurIPS Evaluations & Datasets Track. Contains 100 base tasks and variants across 4 domains (Retail, Travel, Finance, DevOps) with 20 disruption types and 9 disruption profiles. | http://mlcommons.org/croissant/1.0 | https://github.com/Kavirubc/AgentDisruptBench | https://opensource.org/licenses/MIT | 0.1.0 | 2026-04-03T00:00:00 | {
"@type": "sc:Organization",
"name": "AgentDisruptBench Contributors"
} | [
"AI agents",
"benchmarks",
"resilience",
"tool-calling",
"disruptions",
"evaluation",
"LLM",
"fault-injection",
"reliability"
] | false | [
{
"@type": "cr:FileObject",
"@id": "retail-tasks",
"name": "retail.yaml",
"description": "20 standard retail domain tasks (difficulty 1-5)",
"contentUrl": "python/agentdisruptbench/tasks/builtin/retail.yaml",
"encodingFormat": "application/x-yaml",
"sha256": "5c00f518f411c868ab8ee81c35c6... | [
{
"@type": "cr:RecordSet",
"@id": "tasks",
"name": "Benchmark Tasks",
"description": "The 100 benchmark tasks across 4 domains and 3 task types.",
"field": [
{
"@type": "cr:Field",
"@id": "tasks/task_id",
"name": "task_id",
"description": "Unique task identi... |
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