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Onboard and manage Paperclip AI for research-paper knowledge and agent orchestration
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Baseado na classificação ocupacional SOC
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.
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 | paperclip |
| description | Onboard and manage Paperclip AI for research-paper knowledge and agent orchestration |
| metadata | {"openclaw":{"emoji":"📎","requires":{"bins":["python3","node","npm","npx"]}}} |
Use Paperclip AI from ScienceClaw to onboard a local Paperclip instance, run health checks, and start the service that provides AI agents with indexed literature and orchestration capabilities.
Paperclip's quickstart command is:
npx paperclipai onboard --yes
python3 {baseDir}/scripts/paperclip.py --action check --format json
python3 {baseDir}/scripts/paperclip.py --action onboard --format json
python3 {baseDir}/scripts/paperclip.py --action onboard --execute --yes --format json
By default this detaches the long-running Paperclip server and returns a PID plus a log file.
python3 {baseDir}/scripts/paperclip.py --action doctor --execute --format json
python3 {baseDir}/scripts/paperclip.py --action run --execute --format json
| Parameter | Description | Default |
|---|---|---|
--action | Operation: check, onboard, doctor, run, or version | check |
--execute | Actually run the Paperclip command; omitted means dry run | false |
--detach | Run long-lived onboard/run commands in the background | true for onboard/run |
--foreground | Keep long-lived commands attached to the current process | false |
--yes | Pass --yes to paperclipai onboard | true |
--run-after-onboard | Pass --run to paperclipai onboard | false |
--repair | Pass --repair to paperclipai doctor | false |
--bind | Optional bind target for onboarding, such as tailnet | - |
--work-dir | Directory where the Paperclip CLI runs | current directory |
--timeout | Command timeout in seconds | 600 |
--wait-seconds | Seconds to watch a detached command before returning | 5 |
--format | Output format: summary or json | summary |
The skill returns a JSON object with:
action: requested operationcommand: command ScienceClaw would run or did runexecuted: whether a command was executedreturncode, stdout, and stderr when executedpid and log_file for detached server runschecks for local Node/npm/npx availabilityonboard --yes uses Paperclip's non-interactive quickstart defaults.