Autoresearchclaw Autonomous Research

# AutoResearchClaw — Autonomous Research Pipeline

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.

AutoResearchClaw is a fully autonomous 23-stage research pipeline that takes a natural language topic and produces a complete academic paper: real arXiv/Semantic Scholar citations, sandboxed experiments, statistical analysis, multi-agent peer review, and conference-ready LaTeX (NeurIPS/ICML/ICLR). No hallucinated references. No human babysitting.

---

## Installation

```bash
# Clone and install
git clone https://github.com/aiming-lab/AutoResearchClaw.git
cd AutoResearchClaw
python3 -m venv .venv && source .venv/bin/activate
pip install -e .

# Verify CLI is available
researchclaw --help
```

**Requirements:** Python 3.11+

---

## Configuration

```bash
cp config.researchclaw.example.yaml config.arc.yaml
```

### Minimum config (`config.arc.yaml`)

```yaml
project:
  name: "my-research"

research:
  topic: "Your research topic here"

llm:
  provider: "openai"
  base_url: "https://api.openai.com/v1"
  api_key_env: "OPENAI_API_KEY"
  primary_model: "gpt-4o"
  fallback_models: ["gpt-4o-mini"]

experiment:
  mode: "sandbox"
  sandbox:
    python_path: ".venv/bin/python"
```

```bash
export OPENAI_API_KEY="$YOUR_OPENAI_KEY"
```

### OpenRouter config (200+ models)

```yaml
llm:
  provider: "openrouter"
  api_key_env: "OPENROUTER_API_KEY"
  primary_model: "anthropic/claude-3.5-sonnet"
  fallback_models:
    - "google/gemini-pro-1.5"
    - "meta-llama/llama-3.1-70b-instruct"
```

```bash
export OPENROUTER_API_KEY="$YOUR_OPENROUTER_KEY"
```

### ACP (Agent Client Protocol) — no API key needed

```yaml
llm:
  provider: "acp"
  acp:
    agent: "claude"   # or: codex, gemini, opencode, kimi
    cwd: "."
```

The agent CLI (e.g. `claude`) handles its own authentication.

### OpenClaw bridge (optional advanced capabilities)

```yaml
openclaw_bridge:
  use_cron: true              # Scheduled research runs
  use_message: true           # Progress notifications
  use_memory: true            # Cross-session knowledge persistence
  use_sessions_spawn: true    # Parallel sub-sessions
  use_web_fetch: true         # Live web search in literature review
  use_browser: false          # Browser-based paper collection
```

---

## Key CLI Commands

```bash
# Basic run — fully autonomous, no prompts
researchclaw run --topic "Your research idea" --auto-approve

# Run with explicit config file
researchclaw run --config config.arc.yaml --topic "Mixture-of-experts routing efficiency" --auto-approve

# Run with topic defined in config (omit --topic flag)
researchclaw run --config config.arc.yaml --auto-approve

# Interactive mode — pauses at gate stages for approval
researchclaw run --config config.arc.yaml --topic "Your topic"

# Check pipeline status / resume a run
researchclaw status --run-id rc-20260315-120000-abc123

# List past runs
researchclaw list
```

**Gate stages** (5, 9, 20) pause for human approval in interactive mode. Pass `--auto-approve` to skip all gates.

---

## Python API

```python
from researchclaw.pipeline import Runner
from researchclaw.config import load_config

# Load config and run
config = load_config("config.arc.yaml")
config.research.topic = "Efficient attention mechanisms for long-context LLMs"
config.auto_approve = True

runner = Runner(config)
result = runner.run()

# Access outputs
print(result.artifact_dir)          # artifacts/rc-YYYYMMDD-HHMMSS-<hash>/
print(result.deliverables_dir)      # .../deliverable