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sciclaw

sciclaw is a lightweight, open-source paired-scientist AI assistant that turns your local filesystem into a reproducible research co-worker for literature review, hypothesis-driven experimentation, manuscript drafting, and more.

Decision information

Manual verification pending
Ecosystem category
Claw Agents
Agent class
Research
Lineage
Independent
Runs
Local
Autonomy
Autonomous
Content type
Product
Pricing
Open Source
Open source
Yes
License
Not recorded
Maintenance
Unknown
Install methods
Source
Platforms
Not recorded

Documented Claw signals

View inclusion standard →
Multi-step goalsAutonomous execution

Security signals (informational, not a security certification)

Source available

Overview

sciclaw (often styled as sciClaw) is an open-source, paired-scientist AI assistant designed specifically for rigorous scientific research workflows. Built as a lightweight Go binary (~17 MB), it extends frameworks like PicoClaw to act as an autonomous research co-worker that lives inside your project directory.

It connects to major LLM providers (or bring-your-own models), proposes and executes hypothesis-driven research loops, handles literature searches (e.g., PubMed), drafts and revises manuscripts in Word with tracked changes, manages references, and logs every action for full reproducibility.

Key Features

  • Lightweight Local Runtime: Runs as a native Go binary on macOS, Linux, and Windows (including WSL) with minimal dependencies.
  • Scientific Skills: Includes 12+ baseline research-focused tools such as PubMed search, experiment provenance tracking, manuscript co-authoring, and data analysis support.
  • Reproducibility First: Automatically logs all actions, decisions, and outputs in a structured workspace for verifiable science.
  • Manuscript Integration: Directly edits Microsoft Word documents with tracked changes and handles reference management.
  • LLM Flexibility: Supports ChatGPT, Claude, and other providers; no vendor lock-in.
  • Lifecycle Hooks & Autonomy: Hypothesis proposal, experiment design, execution, and iterative improvement in closed-loop workflows.
  • Easy Installation: Available via pre-compiled binaries, source build, or Docker.

Installation

Binary Download

Pre-compiled binaries for multiple platforms are available on the GitHub Releases page.

Homebrew / Source

git clone https://github.com/drpedapati/sciclaw.git
cd sciclaw
make deps && make install

Docker Support

Full Docker setup instructions are provided in the repository for sandboxed execution.

Use Cases

  • Literature Review & Synthesis: Automated PubMed searches and summary generation.
  • Experiment Planning & Execution: Hypothesis-driven loops with provenance tracking.
  • Manuscript Preparation: AI-assisted drafting and revision in Word with change tracking.
  • Reproducible Workflows: Full audit logs for academic publishing and collaboration.
  • Daily Research Companion: Acts as a persistent co-worker embedded in your project filesystem.

Technical Details

sciclaw is MIT-licensed and emphasizes privacy and control by running locally. It integrates deeply with your filesystem, turning directories into intelligent research environments while maintaining strict logging for scientific integrity.

A setup tutorial video is available on YouTube for quick onboarding.

Related Projects

sciclaw builds upon or relates to the broader OpenClaw/PicoClaw ecosystem of local AI agents.

Tags

airesearchscientificagentgoopen-sourcereproducible-researchpubmedmanuscriptllm