🐈 ClawPhD

March 25, 2026 Β· View on GitHub

An OpenClaw Agent for research that can turn academic papers into publication-ready diagrams, posters, videos, and more. This project is based on the nano version of OpenClaw: Nanobot.

License: MIT Python 3.11+

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Features

  • Diagram Generation β€” Create publication-quality academic illustrations and statistical plots from paper sections
  • Figure Reference Extraction β€” Search influential papers and extract real figures as editable SVG + PPTX
  • PDF β†’ Markdown + Editable Figures β€” Convert any paper PDF to structured Markdown; export all labelled figures as PNG + SVG + drawio
  • AI Paper Review β€” Peer-review any PDF against NeurIPS / ICLR / ICML / EuroSys / CVPR rubrics; produces narrative feedback + dimensional scores + Accept/Reject
  • Paper Discovery β€” Proactively search and summarize trending AI papers on a schedule
  • Video Explainers β€” Generate walkthrough videos from paper content
  • Paper Websites β€” Turn papers into interactive web pages
  • Poster Generation β€” Produce conference-ready posters from papers
  • Code Synthesis β€” Extract and generate reproducible code from paper methodologies

Examples

Diagram Generation

examples/diagram_generation_command.sh

Generated results: The following images demonstrate the Agent's iterative refinement process for generating a HumanLLM framework diagram:

First Generation (Initial Output): Initial Generation

After 3 iterations: Iteration v3

These examples showcase how the Agent progressively improves diagram quality through human-in-the-loop feedback, resulting in more polished and publication-ready outputs.

Paper Website Generation

The Agent can turn academic papers into interactive web pages:

examples/page_generation_command.sh

Paper Website Example

Figure Reference Extraction

The Agent searches influential papers and extracts all labelled figures into an editable reference pack (PNG + SVG + PPTX):

examples/figure_ref_command.sh

Figure Reference Preview

PDF to Markdown + Editable Figures

Convert a local paper PDF into structured Markdown and export figure assets (PNG + SVG + drawio, with editable rebuild fallback):

examples/pdf2md_command.sh

Typical output folder:

~/.clawphd/workspace/outputs/pdf2md/<pdf_stem>/

AI Paper Review

Review any paper PDF against real conference rubrics β€” produces a structured narrative review (Synopsis, Strengths, Weaknesses, Suggestions, References) plus venue-specific dimensional scores and an Accept/Reject recommendation:

examples/ai_review_command.sh

Supported venues: NeurIPS Β· ICLR Β· ICML Β· EuroSys Β· OSDI Β· SOSP Β· CVPR Β· ICCV Β· General

Accuracy check β€” ICLR 2024 papers:

PaperReal outcomeOriginalitySignificanceContributionOverallDecision
Mamba (arXiv:2312.00752)Accepted (Spotlight)4 / 44 / 44 / 48 / 10Accept
SELF-RAG (arXiv:2310.11511)Rejected from ICLR ΒΉ3 / 43 / 43 / 47 / 10Accept

ΒΉ Note on SELF-RAG: This is a high-quality paper β€” it was accepted at EMNLP 2023 and has thousands of citations. Its ICLR 2024 rejection was due to a venue policy (already published elsewhere), not a reflection of paper quality. Our system correctly evaluates it as solid, well-executed research (7/10), just not at the same level of architectural breakthrough as Mamba (8/10, with three dimensions at 4/4).

The accepted paper (Mamba) scores higher on every breakthrough dimension. All three dimensions where Mamba achieves 4/4 β€” Originality, Significance, Contribution β€” are the strongest predictors of lasting architectural influence. SELF-RAG scores a uniform 3/4, reflecting solid incremental work. Full review texts: Mamba Β· SELF-RAG.

Output folder:

~/.clawphd/workspace/outputs/paper_review/<pdf_stem>/
β”œβ”€β”€ review.md    # 6-section narrative + score table
└── meta.json    # venue, mode, scores, elapsed time

Quick Start

1. Install

# From source
uv pip install -e .

# Or from PyPI
pip install clawphd-ai

2. Initialize

clawphd onboard

This creates ~/.clawphd/config.json and a default workspace at ~/.clawphd/workspace/.

3. Configure API Key

Edit ~/.clawphd/config.json and add at least one LLM provider key:

{
  "providers": {
    // Pick one (or more):
    "openrouter": { "apiKey": "sk-or-..." },
    "anthropic":  { "apiKey": "sk-ant-..." },
    "openai":     { "apiKey": "sk-..." },
    "gemini":     { "apiKey": "AI..." },
    "deepseek":   { "apiKey": "sk-..." }
  },
  "agents": {
    "defaults": {
      "model": "anthropic/claude-opus-4-5"
    }
  }
}

For PaperBanana diagram generation, also set the Replicate token:

export REPLICATE_API_TOKEN="r8_..."

4. Chat

# Single message
clawphd agent -m "Hello!"

# Interactive REPL
clawphd agent

CLI Reference

CommandDescription
clawphd onboardInitialize config and workspace
clawphd agent [-m MSG]Chat with the agent (interactive if no -m)
clawphd gateway [-p PORT]Start the multi-channel gateway
clawphd statusShow config, API keys, and workspace status
clawphd channels statusShow channel connection status
clawphd channels loginLink WhatsApp via QR code
clawphd cron listList scheduled jobs
clawphd cron addAdd a scheduled job (--every, --cron, or --at)
clawphd cron remove <ID>Remove a scheduled job
clawphd cron enable <ID>Enable / --disable a job
clawphd cron run <ID>Manually trigger a job