// Read a CSV or XLSX file and return columns, shape, dtypes, and first N rows as JSON.
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
Execute arbitrary Python code and return stdout. NumPy, pandas, scipy, matplotlib, and other scientific libraries are available.
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
| name | csv-read |
| description | Read a CSV or XLSX file and return columns, shape, dtypes, and first N rows as JSON. |
Load a CSV or Excel file using pandas and return a JSON preview including column names, shape, data types, and the first N rows.
python3 scripts/csv_read.py --path /data/results.csv --max-rows 50
JSON with keys: columns, shape, dtypes, data (list of rows).