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title: HyperBrickCaseOps Agent Guide
---
# HyperBrickCaseOps Agent Guide
This environment evaluates real-world customer support triage. Agents must classify the ticket, request missing info when required, draft the customer reply, add an internal note, and submit only when the workflow is complete.
## Quick Start (Agent Strategy)
Recommended action order:
1. `classify` — set `queue`, `priority`, `issue_type`
2. `request_info` if `required_next_actions` includes it
3. `wait` if the customer follow-up is pending
4. `draft_reply`
5. `add_internal_note`
6. `submit`
## Environment API
The environment follows the standard OpenEnv API:
- `reset()` -> initial observation
- `step(action)` -> next observation, reward, done
- `state()` -> internal state snapshot
Server entrypoint:
- `server.app:app`
## Action Schema
Each step takes a typed `SupportDeskAction`:
- `operation`: `classify|request_info|draft_reply|add_internal_note|submit|wait`
- `queue`: string or null
- `priority`: string or null
- `issue_type`: string or null
- `status`: string or null
- `resolution_code`: string or null
- `requested_fields`: list of strings
- `reply`: string or null
- `internal_note`: string or null
## Observation Highlights
The observation includes:
- `task_id`, `difficulty`, `objective`
- `ticket` (customer, tier, region, business impact)
- `knowledge_base` (policy snippets)
- `case` (current triage state)
- `workflow_stage`, `required_next_actions`, `risk_flags`
## Tasks and Difficulty
There are 4 tasks with increasing difficulty:
- `billing_refund_easy` (easy)
- `account_takeover_medium` (medium)
- `api_incident_hard` (hard)
- `regulated_export_exception_hard` (hard)
## Grading and Reward
- Deterministic graders score task completion
- Final scores are clamped to `(0.01, 0.99)`
- Reward provides dense progress signals across the episode
## Routing Guide (High-Level)
- Duplicate charge -> `billing_ops`, `high`, `duplicate_charge`
- Suspicious login -> `trust_and_safety`, `urgent`, `account_compromise`
- Production 500s -> `platform_engineering`, `urgent`, `production_incident`
- Export policy bypass -> `compliance_ops`, `high`, `regulated_exception`
## Required Environment Variables
Baseline inference uses:
- `API_BASE_URL`
- `MODEL_NAME`
- `HF_TOKEN`
## Mandatory Stdout Format
The inference script must emit exactly:
```
[START] task=<task_name> env=<benchmark> model=<model_name>
[STEP] step=<n> action=<action_str> reward=<0.00> done=<true|false> error=<msg|null>
[END] success=<true|false> steps=<n> score=<score> rewards=<r1,r2,...,rn>
```
Rules:
- One `[START]` at episode begin
- One `[STEP]` per env step
- One `[END]` after episode close
- `reward` and `rewards` formatted to 2 decimals
- `done`/`success` are lowercase booleans
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