plan/README.md

SentinelOps Arena -- Build Plan

Overview

14-hour hackathon build plan for a multi-agent self-play RL environment on OpenEnv 0.2.1. Solo developer. Deadline: Sunday March 8, 2026 at 1:00 PM.

KEY INSIGHT: Innovation (40%) + Storytelling (30%) = 70% of judging is NON-code. Allocate time accordingly.

Revised Phase Summary

Phase	File	Time	Cumulative	What
0	(inline)	0.5h	0-0.5h	Test H100/Northflank, write 60s video script
1	phase-1-models-and-systems.md	3.5h	0.5-4h	Pydantic models + enterprise system simulators
2	phase-2-environment-core.md	2h	4-6h	SentinelOpsArena(MCPEnvironment), rewards, turn management
3	phase-3-mcp-and-server.md	0.5h	6-6.5h	MCP tools via MCPEnvironment + HTTP server
4	phase-4-demo-and-ui.md	2h	6.5-8.5h	Demo script, Gradio app (1 tab), HF Spaces deploy
5	phase-5-training.md	2h	8.5-10.5h	Colab notebook, GRPO pipeline (fall back to SFT at 1.5h)
6	phase-6-polish-and-submit.md	3.5h	10.5-14h	Polish, video recording, submission

Total: 14 hours

Phase 0: Pre-Flight (Hour 0-0.5)

Before writing any code:

1. Test H100 via Northflank -- verify access, note available VRAM. If no H100, lock to Qwen2.5-1.5B.
2. Write 60-second video script -- forces clarity on what to demo. Script drives the build.
3. Set up repo structure -- create directories, pyproject.toml

Dependencies

Phase 0 (Pre-Flight)
    |
    v
Phase 1 (Models & Systems)
    |
    v
Phase 2 (Environment Core)  -- CHECKPOINT 1 (Hour 6): Minimum Viable
    |
    v
Phase 3 (MCP + Server)      -- MCPEnvironment handles this almost free
    |
    v
Phase 4 (Demo & UI)         -- CHECKPOINT 2 (Hour 8.5): Deploy to HF Spaces
    |
    v
Phase 5 (Training)          -- CHECKPOINT 3 (Hour 10.5): Strong Submission
    |
    v
Phase 6 (Polish & Submit)   -- CHECKPOINT 4 (Hour 14): Full Submission

Stop-and-Submit Checkpoints

Hour 6 (after Phase 2): Environment works with random agents. Submit with basic demo + placeholder training notebook. Minimum viable.

Hour 8.5 (after Phase 4): Environment + MCP tools + Gradio demo deployed on HF Spaces. Good submission. INSURANCE SUBMISSION -- deploy to HF Spaces here.

Hour 10.5 (after Phase 5): Everything above + working Colab training pipeline with visible reward improvement. Strong submission.

Hour 14 (after Phase 6): Polished demo, training curves, video, stretch goals. Full submission.

Scoring Priorities

Criterion	Weight	Primary Phase	Time Allocated
Innovation	40%	Phases 1-2 (3-agent self-play architecture)	5.5h
Storytelling	30%	Phase 4 + 6 (Gradio demo + video)	5.5h
Training Script	20%	Phase 5 (Colab GRPO notebook)	2h
Pipeline	10%	Phase 3 (MCP integration)	0.5h

Key Technical Decisions

• OpenEnv version: 0.2.1 (stable, openenv-core[core]>=0.2.0)
• Base class: MCPEnvironment (NOT raw Environment) -- auto-routes ListToolsAction/CallToolAction to FastMCP server. Gives MCP tool discovery for free.
• MCP-X gateway: CUT -- MCPEnvironment already handles MCP tool exposure. Per-agent isolation is nice-to-have, not needed.
• Action pattern: Action(extra='forbid') -- all agent-specific fields must be Optional with defaults, or use separate action classes per role
• Server: create_app() from openenv.core.env_server.http_server
• Training: Unsloth for model loading only, vanilla TRL GRPOTrainer with rollout_func. Fall back to SFT if GRPO fails at 1.5h.
• Model: Qwen2.5-1.5B for Colab (5GB VRAM), Qwen2.5-7B if H100 available
• Demo: Gradio on HuggingFace Spaces
• Episode scope: 30 ticks, 15 customers, 15 invoices, 10 tickets, 30 tasks
• Attack types: 4 (schema drift, policy drift, social engineering, rate limiting)
• Reserved tool names: reset, step, state, close CANNOT be used as MCP tool names

File Structure

sentinelops_arena/
  __init__.py
  models.py              # Pydantic models (enums, data, action/observation/state)
  systems/
    __init__.py
    crm.py               # CRM simulator
    billing.py           # Billing simulator
    ticketing.py         # Ticketing simulator
  attacks.py             # Attack mechanics (4 types)
  rewards.py             # Reward functions (3 agents)
  task_generator.py      # Task generation
  environment.py         # SentinelOpsArena(MCPEnvironment) -- MCP tools defined here
  server.py              # create_app() HTTP server

training/
  colab_training.ipynb   # Colab GRPO notebook (REQUIRED)
  env_standalone.py      # Standalone env for Colab (no openenv dependency)

app.py                   # HF Spaces Gradio entry point
pyproject.toml
README.md

NOTE: No separate mcp_tools.py -- MCP tools are defined inside environment.py using FastMCP, and MCPEnvironment auto-routes them.

NOTE: No mcp-x/ directory -- MCP-X gateway is CUT from the plan.

Partner Track Alignment

• Fleet AI (Scalable Oversight): The Oversight agent monitors, analyzes, and explains behavior of Worker agent
• Patronus AI (Schema Drift): Schema drift and policy drift are core attack types in the environment