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Scientific Problem Selection

Official
anthropics·vlatest·other

This skill helps identify relevant scientific problems for exploration by analyzing complex data and prioritizing impactful research areas.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add anthropics/life-sciences --skill scientific-problem-selection -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

anthropics

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned anthropics/life-sciences at e96556b637.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
e96556b637
Manifest
scientific-problem-selection/SKILL.md
Scanned
11 files, 2,768 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill helps identify and prioritize scientific problems for research. It can analyze a broad area of science, suggest specific problems within that field, and rank them based on factors like potential impact and feasibility. The tool aims to accelerate the process of finding valuable and actionable research questions.

When to use it

  • Brainstorming initial research directions in a new scientific domain.
  • Identifying gaps in existing knowledge within a specific area of study.
  • Prioritizing potential research projects based on impact and feasibility assessments.
  • Generating novel hypotheses for experimental investigation.

Key capabilities

  • Scientific problem identification
  • Problem prioritization
  • Domain analysis
  • Hypothesis generation

Example prompts

  • "Suggest three high-impact problems in the field of synthetic biology."
  • "What are some promising research questions related to Alzheimer's disease?"
  • "Rank potential cancer research topics by feasibility and potential impact."

Tips & gotchas

The skill’s effectiveness depends on providing a sufficiently broad and well-defined scientific domain. Results may require refinement based on expert judgment and further investigation.