dev-env-debugger / openenv.yaml
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add task4/task5 to openenv.yaml
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name: dev-env-debugger
version: 1.0.0
description: >
An OpenEnv environment where an AI agent debugs a broken multi-service
development stack. The agent must read logs, inspect configs, fix
environment variables, and restart services to restore a healthy state.
tags:
- openenv
- devops
- debugging
- real-world
- multi-service
author: Ajinkya
license: MIT
environment:
reset_endpoint: /reset
step_endpoint: /step
state_endpoint: /state
tasks_endpoint: /tasks
grader_endpoint: /grader
baseline_endpoint: /baseline
tasks:
- id: task1
name: Single Service Fault
difficulty: easy
description: One service down due to a single misconfigured environment variable.
- id: task2
name: Multi-Fault Diagnosis
difficulty: medium
description: Two services failing due to independent faults. Partial credit per fault fixed.
- id: task3
name: Cascading Failure Debug
difficulty: hard
description: Root cause fault causing cascading failures with misleading error messages.
- id: task4
name: Triple Fault Storm
difficulty: hard
description: Three simultaneous independent faults across all services. Agent must triage and fix all three.
- id: task5
name: Silent Misconfiguration
difficulty: expert
description: Two faults with no obvious error logs. Agent must inspect env vars proactively, not rely on logs.
observation_space:
type: object
fields:
step: integer
services: object # map of service name β†’ {status, port}
last_action_result: object # {success: bool, message: string}
available_actions: array
done: boolean
action_space:
type: object
fields:
type: string # read_logs | inspect_env | edit_env | restart_service | run_healthcheck | submit
service: string # optional β€” api | worker | database | proxy
key: string # optional β€” env var key (edit_env only)
value: string # optional β€” env var value (edit_env only)
reward:
min: -0.5
max: 1.0
shaped: true
description: >
Partial rewards for correct diagnostic actions and service recovery.
Penalties for redundant actions and submitting while unhealthy.
baseline:
model: gpt-4o-mini
expected_scores:
task1: 0.85
task2: 0.60
task3: 0.35