Manage SciencePal research agent runs and sandbox files via REST APIs.
npx skills add https://github.com/x-zheng16/cc-sciencepal --skill sciencepal
Please help me install this Agent Skill. Skill: sciencepal Source: https://github.com/x-zheng16/cc-sciencepal/tree/main/skills/sciencepal Command: npx skills add https://github.com/x-zheng16/cc-sciencepal --skill sciencepal
This Skill eliminates the manual overhead of launching, tracking, and managing AI-powered science research agent tasks across staging and production environments, letting researchers focus on interpreting results instead of coordinating workflow steps.
Use the sciencepal skill to start a new materials science analysis task to calculate the band gap of Li2FePO4 and download the results when it finishes.
High-intent search queries and answers about installing and using this skill.
Managing AI science research agent sessions involves starting, tracking, and stopping workflows for biology, materials science, and patent analysis. You can orchestrate end-to-end runs across staging and production environments, monitor status, and handle compute sandbox files.
Yes, you can browse, upload, download, and delete files in agent compute sandboxes. This allows direct access to input data, intermediate results, and final deliverables generated during science research agent runs.
Supported scientific domains include biology, materials science, protein structural biology, plasma physics, and patent analysis. The orchestration applies domain-specific guidance and prompt engineering tips to improve result quality for these specific research tasks.
Starting a protein structural biology analysis task requires initiating an agent run for a specific target, then monitoring its run status. Once the task completes, you can download the generated report and supporting data files from the sandbox.
Yes, session tracking and status monitoring require authenticated REST API integrations. These integrations satisfy functional requirements for starting agent runs, following up on existing sessions, and managing compute sandbox files securely.
Handling failed runs involves applying tailored error recovery steps provided for common science research workflows. These domain-specific guidance steps reduce failed runs by improving prompt engineering and managing workflow coordination automatically.
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