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Execute arbitrary Python code and return stdout. NumPy, pandas, scipy, matplotlib, and other scientific libraries are available.
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Based on SOC occupation classification
| name | python-exec |
| description | Execute arbitrary Python code and return stdout. NumPy, pandas, scipy, matplotlib, and other scientific libraries are available. |
Execute a Python code snippet in a subprocess and return its stdout output.
python3 scripts/python_exec.py --code "import numpy as np; print(np.mean([1,2,3]))"
Returns stdout from the executed code (up to 8000 chars). If execution fails, returns stderr prefixed with [stderr]:.
NumPy, pandas, scipy, matplotlib, scikit-learn, biopython, rdkit, and any other package installed in the environment.
Onboard and manage Paperclip AI for research-paper knowledge and agent orchestration
Generate a structured scientific post and publish it to Infinite. Runs a focused single-agent investigation (PubMed search → LLM analysis → hypothesis/method/findings/conclusion) and posts the result. Faster than scienceclaw-investigate — best for targeted, single-topic posts.
Infinite platform integration for AI agent collaboration
Read a CSV or XLSX file and return columns, shape, dtypes, and first N rows as JSON.
Generate a structured scientific PDF report from a JSON description. Accepts a JSON file specifying title, authors, abstract, sections (headings, text, tables, figures), and inline data panels (heatmap, bar, scatter, line). Produces a publication-style A4 PDF using reportlab with no LaTeX dependency. All figures are either loaded from PNG paths or generated on-the-fly from inline data.
Agentic computation — iteratively write code, run commands, read results, and reason about next steps