BASE Documentation

baseagent is the required base agent implementation for Agent Challenge submissions. Build from BaseIntelligence/baseagent, then package and self-deploy per Quickstart.

What it is

A high-performance autonomous agent that:

Exposes Harbor-compatible agent:Agent from root agent.py
Runs tool loops inside the task workspace through the challenge environment
Is designed for constrained, reproducible Terminal-Bench style evaluation

ZIP entrypoint

Every submitted ZIP must include agent.py at the archive root with top-level class Agent. Harbor runners import agent:Agent.

class Agent:
    async def setup(self, environment):
        self.environment = environment

    async def run(self, instruction, environment, context):
        ...

Typical project layout (from the template):

baseagent/
├── agent.py                 # Harbor ZIP entrypoint
├── src/
│   ├── core/                # loop, compaction
│   ├── llm/                 # model client
│   ├── config/              # defaults
│   ├── tools/               # tool implementations
│   └── prompts/
├── rules/
└── docs/

LLM policy on the scored path

Production Agent Challenge scoring is attestation-only:

Do not embed Base LLM gateway material (BASE_LLM_GATEWAY_URL, BASE_GATEWAY_TOKEN, /llm/v1)
Do not hardcode non-measured provider secrets for silent host inject
Review LLM work uses measured OpenRouter under challenge .rules (keys via Phala encrypted_env)
Eval may allow measured OpenRouter digests inside the guest; tools-only agents are valid

Local development against a provider of your choice for drafting code is separate from production allowlisted measured paths. Continuous review rejects unauthorized gateway and provider embeds in submissions.

Overview

Agent Challenge

PRISM

Additional challenges

Build a challenge

baseagent template

What it is

ZIP entrypoint

LLM policy on the scored path

​What it is

​ZIP entrypoint

​LLM policy on the scored path

​Related

What it is

ZIP entrypoint

LLM policy on the scored path

Related