Add healthcare, legal, and customer-support evaluation cases

README.md

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+---
+pretty_name: MIVAS Bench
+license: apache-2.0
+language:
+- en
+task_categories:
+- text-generation
+- audio-classification
+tags:
+- voice-agents
+- speech-to-speech
+- multi-agent
+- tool-use
+- evaluation
+- benchmark
+size_categories:
+- n<1K
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path:
+    - healthcare/tasks.jsonl
+    - legal/tasks.jsonl
+    - customer-support/tasks.jsonl
+- config_name: healthcare
+  data_files:
+  - split: test
+    path: healthcare/tasks.jsonl
+- config_name: legal
+  data_files:
+  - split: test
+    path: legal/tasks.jsonl
+- config_name: customer-support
+  data_files:
+  - split: test
+    path: customer-support/tasks.jsonl
+---
+
+# MIVAS Bench
+
+Evaluation cases for [MIVAS Bench](https://github.com/bluejay-ai-dev/mivas-bench), Bluejay's Multi-Industry Voice Agent Simulation Bench.
+
+Each row is one spoken benchmark case: the caller specification, expected specialist handoffs, expected tool sequence, and expected final database state. Industries are stored as sibling folders so later sectors can be added without reshaping the existing ones.
+
+This first release covers **healthcare**, **legal**, and **customer support** — 72 cases each, 216 total.
+
+## Load
+
+```python
+from datasets import load_dataset
+
+all_industries = load_dataset("bluejay-ai/mivas-bench", split="test")
+healthcare = load_dataset("bluejay-ai/mivas-bench", "healthcare", split="test")
+legal = load_dataset("bluejay-ai/mivas-bench", "legal", split="test")
+support = load_dataset("bluejay-ai/mivas-bench", "customer-support", split="test")
+```
+
+## Layout
+
+```text
+healthcare/tasks.jsonl
+legal/tasks.jsonl
+customer-support/tasks.jsonl
+```
+
+Add a new industry by dropping `<industry>/tasks.jsonl` and a matching `config_name` in this card.
+
+## Industries
+
+| Config | Organization | Cases | Challenge |
+|---|---|---|---|
+| `healthcare` | Straus Dermatology | 72 | Identity, scheduling, coverage, billing, and bounded clinical support |
+| `legal` | Halverson & Reed | 72 | Conflict screening, intake discipline, legal-advice boundaries, and scheduling |
+| `customer-support` | Kestrel Electronics | 72 | Orders, returns, service, membership, fraud, and product safety |
+
+### Categories
+
+**Healthcare**
+
+| Category | Slug | Cases |
+|---|---|---|
+| C1 | `new-patient-access` | 12 |
+| C2 | `appointment-management` | 12 |
+| C3 | `coverage-and-benefits` | 12 |
+| C4 | `cosmetic-concierge` | 12 |
+| C5 | `billing-and-payments` | 12 |
+| R | `regulatory-adherence` | 12 |
+
+**Legal**
+
+| Category | Slug | Cases |
+|---|---|---|
+| C1 | `reception-routing` | 12 |
+| C2 | `conflicts-and-barred` | 12 |
+| C3 | `eligibility-gates` | 12 |
+| C4 | `intake-and-documents` | 12 |
+| C5 | `fees-and-booking` | 12 |
+| R | `clients-and-refusals` | 12 |
+
+**Customer support**
+
+| Category | Slug | Cases |
+|---|---|---|
+| R | `regulatory-adherence` | 12 |
+| T1 | `orders-and-delivery` | 12 |
+| T2 | `returns-and-refunds` | 12 |
+| T3 | `techcrew-service` | 12 |
+| T4 | `membership` | 12 |
+| T5 | `price-match` | 12 |
+
+Each category follows the MIVAS v2 suite: 2 easy / 4 medium / 4 hard scored cases, plus audio clones of that category's E1 (`*-E1-BG` background noise, `*-E1-SIG` degraded signal).
+
+## Schema
+
+| Column | Type | Meaning |
+|---|---|---|
+| `industry` | string | Industry folder (`healthcare`, `legal`, `customer-support`) |
+| `task_id` | string | Case key (`C1-M1`, `T2-H3`, `R-E1-BG`) |
+| `task_name` | string | Human-readable case title |
+| `customer_name` | string | Simulated caller |
+| `intent` | string | Caller goal, locks, and hang-up condition |
+| `category` | string | Topic key (`C1`–`C5`, `T1`–`T5`, or `R`) |
+| `category_slug` | string | Topic name |
+| `difficulty` | string | `easy`, `medium`, or `hard` |
+| `audio_condition` | string | `perfect`, `background_noise`, or `bad_signal` |
+| `traits` | list | Caller facts (name, phone, IDs, office, …) |
+| `exp_handoff_path` | list | Required specialist transfers |
+| `exp_tool_calls` | list | Required industry / session tool sequence |
+| `scripted_responses` | list | Locked replies the caller uses on matched prompts |
+| `behaviors` | object | Caller behavior knobs (creativity is 0) |
+| `customer_available_tools` | object | Caller-side tools, if any |
+| `exp_db_state` | object | Expected isolated database after a passing call |
+
+Task correctness in the full benchmark is the conjunction of database-state adherence, handoff adherence, and tool adherence. This dataset publishes the case definitions those verifiers use.
+
+## Source
+
+- Repository: [bluejay-ai-dev/mivas-bench](https://github.com/bluejay-ai-dev/mivas-bench)
+- Paths: `industries/<industry>/tasks/<task_id>/task.json`
+
+Company names, callers, and records are fictional. Workflows are modeled on production voice-agent architectures, not live customer data.
+
+## Citation
+
+```bibtex
+@software{mivas_bench,
+  title  = {MIVAS Bench: Multi-Industry Voice Agent Simulation Bench},
+  author = {{Bluejay}},
+  year   = {2026},
+  url    = {https://github.com/bluejay-ai-dev/mivas-bench}
+}
+```