Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
INBOX: struct<folder: string, delimiter: string, flags: list<item: null>, sim_clock: timestamp[s], owner_ad (... 775 chars omitted)
child 0, folder: string
child 1, delimiter: string
child 2, flags: list<item: null>
child 0, item: null
child 3, sim_clock: timestamp[s]
child 4, owner_address: string
child 5, messages: list<item: struct<message_id: string, template_id: string, label: string, subject: string, from_addr (... 649 chars omitted)
child 0, item: struct<message_id: string, template_id: string, label: string, subject: string, from_addr: string, t (... 637 chars omitted)
child 0, message_id: string
child 1, template_id: string
child 2, label: string
child 3, subject: string
child 4, from_addr: string
child 5, to_addr: list<item: string>
child 0, item: string
child 6, cc_addr: list<item: null>
child 0, item: null
child 7, bcc_addr: list<item: null>
child 0, item: null
child 8, date: timestamp[s]
child 9, body_text: string
child 10, body_html: null
child 11, is_read: bool
child 12, is_important: bool
child 13, is_flagged: bool
child 14, in_reply_to: null
child 15, references_header: null
child 16, headers: struct<X-Fitout-Template: string, X-Fitout-Provider-Id: string, X-Fitout-Quote-Total: string, X-Fito (... 207 chars omitted)
...
rs: struct<>
child 15, created: timestamp[s]
child 16, updated: timestamp[s]
work_windows: struct<calendar_id: string, owner: string, timezone: string, sim_clock: timestamp[s], events: list<i (... 412 chars omitted)
child 0, calendar_id: string
child 1, owner: string
child 2, timezone: string
child 3, sim_clock: timestamp[s]
child 4, events: list<item: struct<id: string, summary: string, description: string, location: string, start_datetime (... 317 chars omitted)
child 0, item: struct<id: string, summary: string, description: string, location: string, start_datetime: timestamp (... 305 chars omitted)
child 0, id: string
child 1, summary: string
child 2, description: string
child 3, location: string
child 4, start_datetime: timestamp[s]
child 5, start_timezone: string
child 6, end_datetime: timestamp[s]
child 7, end_timezone: string
child 8, status: string
child 9, html_link: null
child 10, creator: struct<email: string>
child 0, email: string
child 11, organizer: struct<email: string>
child 0, email: string
child 12, attendees: list<item: null>
child 0, item: null
child 13, recurrence: list<item: string>
child 0, item: string
child 14, reminders: struct<>
child 15, created: timestamp[s]
child 16, updated: timestamp[s]
to
{'events': {'calendar_id': Value('string'), 'owner': Value('string'), 'timezone': Value('string'), 'sim_clock': Value('timestamp[s]'), 'events': List({'id': Value('string'), 'summary': Value('string'), 'description': Value('string'), 'location': Value('string'), 'start_datetime': Value('timestamp[s]'), 'start_timezone': Value('string'), 'end_datetime': Value('timestamp[s]'), 'end_timezone': Value('string'), 'status': Value('string'), 'html_link': Value('null'), 'creator': {'email': Value('string')}, 'organizer': {'email': Value('string')}, 'attendees': List({'email': Value('string'), 'responseStatus': Value('string')}), 'recurrence': List(Value('string')), 'reminders': {}, 'created': Value('timestamp[s]'), 'updated': Value('timestamp[s]')})}, 'work_windows': {'calendar_id': Value('string'), 'owner': Value('string'), 'timezone': Value('string'), 'sim_clock': Value('timestamp[s]'), 'events': List({'id': Value('string'), 'summary': Value('string'), 'description': Value('string'), 'location': Value('string'), 'start_datetime': Value('timestamp[s]'), 'start_timezone': Value('string'), 'end_datetime': Value('timestamp[s]'), 'end_timezone': Value('string'), 'status': Value('string'), 'html_link': Value('null'), 'creator': {'email': Value('string')}, 'organizer': {'email': Value('string')}, 'attendees': List(Value('null')), 'recurrence': List(Value('string')), 'reminders': {}, 'created': Value('timestamp[s]'), 'updated': Value('timestamp[s]')})}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
INBOX: struct<folder: string, delimiter: string, flags: list<item: null>, sim_clock: timestamp[s], owner_ad (... 775 chars omitted)
child 0, folder: string
child 1, delimiter: string
child 2, flags: list<item: null>
child 0, item: null
child 3, sim_clock: timestamp[s]
child 4, owner_address: string
child 5, messages: list<item: struct<message_id: string, template_id: string, label: string, subject: string, from_addr (... 649 chars omitted)
child 0, item: struct<message_id: string, template_id: string, label: string, subject: string, from_addr: string, t (... 637 chars omitted)
child 0, message_id: string
child 1, template_id: string
child 2, label: string
child 3, subject: string
child 4, from_addr: string
child 5, to_addr: list<item: string>
child 0, item: string
child 6, cc_addr: list<item: null>
child 0, item: null
child 7, bcc_addr: list<item: null>
child 0, item: null
child 8, date: timestamp[s]
child 9, body_text: string
child 10, body_html: null
child 11, is_read: bool
child 12, is_important: bool
child 13, is_flagged: bool
child 14, in_reply_to: null
child 15, references_header: null
child 16, headers: struct<X-Fitout-Template: string, X-Fitout-Provider-Id: string, X-Fitout-Quote-Total: string, X-Fito (... 207 chars omitted)
...
rs: struct<>
child 15, created: timestamp[s]
child 16, updated: timestamp[s]
work_windows: struct<calendar_id: string, owner: string, timezone: string, sim_clock: timestamp[s], events: list<i (... 412 chars omitted)
child 0, calendar_id: string
child 1, owner: string
child 2, timezone: string
child 3, sim_clock: timestamp[s]
child 4, events: list<item: struct<id: string, summary: string, description: string, location: string, start_datetime (... 317 chars omitted)
child 0, item: struct<id: string, summary: string, description: string, location: string, start_datetime: timestamp (... 305 chars omitted)
child 0, id: string
child 1, summary: string
child 2, description: string
child 3, location: string
child 4, start_datetime: timestamp[s]
child 5, start_timezone: string
child 6, end_datetime: timestamp[s]
child 7, end_timezone: string
child 8, status: string
child 9, html_link: null
child 10, creator: struct<email: string>
child 0, email: string
child 11, organizer: struct<email: string>
child 0, email: string
child 12, attendees: list<item: null>
child 0, item: null
child 13, recurrence: list<item: string>
child 0, item: string
child 14, reminders: struct<>
child 15, created: timestamp[s]
child 16, updated: timestamp[s]
to
{'events': {'calendar_id': Value('string'), 'owner': Value('string'), 'timezone': Value('string'), 'sim_clock': Value('timestamp[s]'), 'events': List({'id': Value('string'), 'summary': Value('string'), 'description': Value('string'), 'location': Value('string'), 'start_datetime': Value('timestamp[s]'), 'start_timezone': Value('string'), 'end_datetime': Value('timestamp[s]'), 'end_timezone': Value('string'), 'status': Value('string'), 'html_link': Value('null'), 'creator': {'email': Value('string')}, 'organizer': {'email': Value('string')}, 'attendees': List({'email': Value('string'), 'responseStatus': Value('string')}), 'recurrence': List(Value('string')), 'reminders': {}, 'created': Value('timestamp[s]'), 'updated': Value('timestamp[s]')})}, 'work_windows': {'calendar_id': Value('string'), 'owner': Value('string'), 'timezone': Value('string'), 'sim_clock': Value('timestamp[s]'), 'events': List({'id': Value('string'), 'summary': Value('string'), 'description': Value('string'), 'location': Value('string'), 'start_datetime': Value('timestamp[s]'), 'start_timezone': Value('string'), 'end_datetime': Value('timestamp[s]'), 'end_timezone': Value('string'), 'status': Value('string'), 'html_link': Value('null'), 'creator': {'email': Value('string')}, 'organizer': {'email': Value('string')}, 'attendees': List(Value('null')), 'recurrence': List(Value('string')), 'reminders': {}, 'created': Value('timestamp[s]'), 'updated': Value('timestamp[s]')})}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Vibelifebench
Benchmark version: 1.1.0
Scoring contract: flat_pool
Long-horizon — 20–30 stages per task, spanning simulated weeks.
Multi-service — 137 task-local environment bindings across 21 services.
Verifiable — 1247 atomic checks reading real backend state, not prose.
Overview
Vibelifebench evaluates agents on the messy, consequential work of managing someone's life over weeks: a lawsuit, a mortgage escrow shortfall, a cross-city apartment hunt, a licensing exam, an office fit-out.
Each task unfolds as a timeline. The user sends messages, the world changes underneath the agent (a hearing gets rescheduled, a price moves, a policy updates), and the agent has to keep goals, constraints, commitments, and open items coherent across every stage — while knowing which actions it may take on its own and which require asking first.
What makes this hard is not any single step. It is that stage 20 depends on what the agent understood at stage 3, and nothing re-states the context along the way.
Task-only release. This repository distributes task bundles only: no service implementations, mock servers, capability framework, or execution engine. Running the tasks requires a compatible Terrarium/OpenClaw runtime and service implementations supplied separately. See External Runtime Requirement.
Tasks
20 tasks across 10 domains, 489 stages, 1247 atomic checks. Every task ships bilingual (zh/en) documentation and is fully self-contained.
| Domain | Task ID | Title | Stages | Envs | Checks | Weight | Difficulty |
|---|---|---|---|---|---|---|---|
| Career / 职业与劳动权益 | career_equity_buyback_recovery |
Equity Buyback Reconciliation and Re-employment | 25 | 7 | 42 | 100 | hard |
| Career / 职业与劳动权益 | career_espp_refund_recovery |
ESPP Redemption Reconciliation and Re-employment | 24 | 7 | 42 | 100 | hard |
| Exam prep / 考试准备 | civil_service_written_to_interview_audit |
Civil Service Written Exam to Interview Qualification Audit | 25 | 9 | 40 | 62 | hard |
| Exam prep / 考试准备 | pharmacist_western_registration_shift_prep |
Licensed Pharmacist Registration, Course Purchase, and Shift-Based Preparation | 30 | 5 | 53 | 89 | hard |
| Finance / 个人金融 | arm_escrow_shortfall_reset_guard_30d |
ARM Escrow Shortfall Reset Guard — 30-Day Plan | 24 | 6 | 123 | 386 | hard |
| Finance / 个人金融 | hsa_medical_bill_liquidity_guard_30d |
HSA Medical Bill Liquidity Guard — 30-Day Plan | 24 | 6 | 123 | 386 | hard |
| Fitness / 运动与体能 | broadcast_exam_posture_breathing_32d |
Broadcast Arts Exam Posture, Breathing, and Taper Maintenance | 26 | 5 | 50 | 82.5 | hard |
| Fitness / 运动与体能 | dragon_boat_newcomer_upper_body_endurance_037 |
Dragon Boat Newcomer Upper-Body Endurance Preparation | 28 | 6 | 44 | 68.5 | hard |
| Litigation / 诉讼管理 | food_safety_dispute_33d |
Food Safety E-commerce Dispute Litigation — 33 Days | 22 | 5 | 51 | 100 | hard |
| Litigation / 诉讼管理 | private_lending_33d |
Private Lending Recovery Litigation — 33 Days | 22 | 5 | 71 | 100 | medium |
| Renovation / 装修与改造 | garage_adu_rental_conversion_25d |
Legal Garage-to-Rental ADU Conversion | 25 | 8 | 45 | 77.5 | medium |
| Renovation / 装修与改造 | office_fitout_15d |
Commercial Office Fit-Out Project Management | 21 | 7 | 105 | 289.657 | hard |
| Rental / 住房租赁 | cross_city_remote_viewing_rental |
Cross-City Remote Viewing Rental and Address Proof | 24 | 8 | 66 | 97.5 | hard |
| Rental / 住房租赁 | wheelchair_student_accessible_rental |
Accessible Campus Housing for a Wheelchair-Using Student | 24 | 8 | 58 | 88.75 | hard |
| Shopping / 购物与履约 | baby_stroller_safety_standard_30d |
Baby Stroller Safety and Accessory Coordination | 24 | 7 | 69 | 134 | medium |
| Shopping / 购物与履约 | central_ac_install_30d |
Central Air-Conditioning Installation and After-Sales Reconciliation | 24 | 7 | 70 | 136.5 | hard |
| Team building / 团队活动 | factory_visit_safety_day |
Supply Chain Factory Visit Team Day | 25 | 7 | 46 | 100 | hard |
| Team building / 团队活动 | pottery_invoice_compliance_day |
Indoor Pottery Team-Building Planning | 25 | 7 | 64 | 100 | medium |
| Travel / 差旅与出行 | east_china_bereavement_docs_reissue |
Low-Disruption Bereavement Travel and Document Reissue Assistance | 22 | 10 | 44 | 100 | hard |
| Travel / 差旅与出行 | galapagos_no_us_transit |
Galapagos Travel Without U.S. Transit | 25 | 7 | 41 | 100 | hard |
Difficulty labels in 1.1.0 are retained from the prior audited release. The scoring contract changed to
flat_pool, but the labels were not recalibrated or re-bucketed for this release: 16 tasks arehard, 4 aremedium, and 0 areeasy.
Envs counts the task's service-environment bindings. Weight is the task's declared
total scoring weight; scores are normalized per task, so weights are not comparable
across tasks.
What a task looks like
# event.yaml — the timeline the runtime replays
stages:
0:
- id: S00_user_initial_request
time: 2026-07-24T09:10:00+08:00
type: user_message
from: 林乔
body: |
我 8 月要去厄瓜多尔参加一个加拉帕戈斯生态数据工作坊...
能 hold 的先 hold,最终付款和不可退项目要先跟我确认。
1:
- id: S01_mutation_workshop_calendar_publish
time: 2026-07-25T09:40:00+08:00
type: mutation # the world changes without being announced
target: calendar_mock
Stages are checkpoints, not calendar days. Event types include user_message,
mutation, notification, world, and policy_update.
Capability Coverage
- Long-horizon state maintenance — keep goals, constraints, commitments, and open items consistent across many stages.
- Tool use — query and act across email, calendar, banking, booking, maps, knowledge-base, and notification services.
- Dynamic world updates — apply staged changes in event order without using future facts early.
- Authorization and risk control — distinguish reads and drafts from payments, orders, cancellations, and other high-impact actions.
- Evidence and traceability — keep business state, tool results, and workspace deliverables in agreement.
- Cross-service coordination — reconcile times, amounts, statuses, identities, policies, and dependencies across services.
Service Coverage
| Service | Tasks | Service | Tasks | Service | Tasks |
|---|---|---|---|---|---|
calendar |
20 | email |
20 | notion |
18 |
notification_hub |
12 | legal_search |
9 | maps |
8 |
review_platform |
7 | banking |
6 | credit_card |
5 |
ecommerce |
5 | weather |
5 | brokerage |
4 |
listing_platform |
4 | hotel_booking |
3 | delivery_logistics |
2 |
flight_booking |
2 | health_tracker |
2 | job_board |
2 |
content_platform |
1 | rail_booking |
1 | visa_and_advisory |
1 |
Repository Structure
Vibelifebench/
├── README.md
└── eval_set/
└── <domain>/
└── <task>/
├── task.py # entrypoint, service binding, event dispatch, aggregation
├── task.md # bilingual public task card
├── task.toml # metadata, dependencies, scenario window, scoring summary
├── event.yaml # stage timeline: user messages, notifications, updates
├── run.toml # runner configuration
├── workspace/ # initial agent workspace and durable deliverables
├── envs/
│ └── <service>/<env_name>/ # task-local seed, env card, staged data
├── mutations/ # standalone staged updates (when present)
└── rubrics/ # formal scoring modules
The repository root contains only README.md and eval_set/. Every environment payload
is task-local; no shared top-level envs/ directory is distributed.
Environments
All 137 bindings use the layout eval_set/<domain>/<task>/envs/<service>/<env_name>/.
Every environment contains a non-empty init.sql and a bilingual README.md; some also
include init.json, JSONL records, or SQL updates referenced by event.yaml. Every SQL
seed was freshly loaded against its service schema and checked with SQLite
integrity_check and foreign-key validation.
Environments are seeded from init.sql at load time, so no database files are committed.
Evaluation
All 20 tasks use flat_pool scoring: atomic checks draw from a single weighted pool,
and the task score is the earned fraction of total weight.
Rubric modules live in rubrics/ and are loaded and aggregated by task.py:
| Module | Scope |
|---|---|
stage_<N>.py |
Per-stage execution |
cross_stage.py |
Consistency across stages |
final.py |
Final deliverables |
_helpers.py |
Shared predicates and backend-state assertions |
Every task provides stage_<N>.py, cross_stage.py, final.py, and _helpers.py;
a few carry additional task-specific helper modules.
Checks are written to read backend state and workspace artifacts rather than reward narration, so describing an action does not earn the credit for performing it.
task.toml records each task's post-cleanup atomic-check count and declared total weight.
External Runtime Requirement
Task content is complete as a bundle, but execution depends on an external runtime. A compatible environment must:
- provide the Terrarium/OpenClaw task APIs referenced by
task.py; - provide implementations and schemas for the declared services;
- load environments from task-local
envs/per[dependencies.envs]intask.toml; - apply
event.yamlevents in stage and time order; - supply workspace persistence, tool traces, and the runtime context the rubrics need.
Set the model in each task's run.toml before running:
[[agents]]
name = "openclaw"
model_name = "<your-provider>/<your-model>"
Synthetic Data and Privacy
All people, organizations, accounts, communications, orders, transactions, places, policy summaries, health records, and other business entities are offline synthetic data. The environments require no internet access and contain no real personal data.
License
No license file is bundled with this task-only release. Use and redistribution are governed by the terms supplied by the publisher for this repository.
Citation
@misc{vibelifebench_2026,
title = {Vibelifebench: A 20-Task Long-Horizon Agent Evaluation Set},
year = {2026},
howpublished = {Task-only release},
note = {Long-horizon agent tasks with task-local synthetic environments}
}
Vibelifebench · Evolvent AI
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