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name: it_mental_health_env
version: "1.0.0"
description: >
A reinforcement learning environment for mental health assessment and
intervention planning in IT and software engineering teams. Agents solve
three progressively harder tasks: burnout detection, stress triage, and
team-level intervention planning. Each task has a deterministic programmatic
grader and returns a normalized reward in the 0.0-1.0 range.
type: typed
runtime:
language: python
version: "3.11"
app:
module: server.app
object: app
port: 7860
tasks:
- id: burnout_detection
difficulty: easy
description: Identify Maslach burnout dimensions and severity from an employee profile
objective: Identify burnout dimensions, severity, top red flags, and HR escalation need from a single employee profile
reward_range: [0.0, 1.0]
grader: burnout_detection_grader
graders:
- burnout_detection_grader
- id: stress_triage
difficulty: medium
description: Triage 3 IT employees by stress tier and recommend immediate actions
objective: Classify three employee cases by urgency, rank intervention priority, and recommend immediate plus 2-week support
reward_range: [0.0, 1.0]
grader: stress_triage_grader
graders:
- stress_triage_grader
- id: intervention_plan
difficulty: hard
description: Design a 4-week mental health intervention plan for a burned-out IT team
objective: Create a four-week intervention plan with owners, KPIs, risk, and budget for a burned-out software team
reward_range: [0.0, 1.0]
grader: intervention_plan_grader
graders:
- intervention_plan_grader
graders:
module: graders
registry: GRADERS
task_grader_pairs: TASK_GRADER_PAIRS
action_space:
type: text
fields:
response: str
task_id: str
confidence: float
metadata: dict
observation_space:
type: text
fields:
scenario: str
feedback: str
reward: float
done: bool
score_breakdown: dict
task_id: str
endpoints:
reset: POST /reset
step: POST /step
state: GET /state
health: GET /health
tasks: GET /tasks
schema: GET /schema
author: "IT Mental Health OpenEnv - Scaler x Meta-PyTorch Hackathon 2026"
license: MIT
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