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Cs Research Methodology

Checked
sundial-org·vlatest·other

This skill provides guidance on research methodologies for CS projects, ensuring robust and well-structured investigations.

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 sundial-org/skills --skill cs-research-methodology -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

sundial-org

Taken from the source listing. We haven't verified who controls this account.

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 sundial-org/skills at 5a3bf9fdc4.

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

Commit
5a3bf9fdc4
Manifest
skills/cs-research-methodology/SKILL.md
Scanned
5 files, 246 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 enables AI agents to apply established computer science research methodologies. It provides guidance on formulating hypotheses, designing experiments, and analyzing results in a rigorous and reproducible manner. The agent can assist with literature reviews, identifying appropriate evaluation metrics, and interpreting findings within the context of existing research.

When to use it

  • Designing an experiment: You need help structuring a test to validate a new algorithm or system design.
  • Literature review: You want assistance in summarizing and synthesizing relevant academic papers for a project.
  • Evaluating results: The agent can provide insights into interpreting experimental data and drawing meaningful conclusions.
  • Reproducibility check: You need help ensuring your research process is documented and repeatable according to best practices.

Key capabilities

  • Hypothesis formulation
  • Experimental design
  • Literature review summarization
  • Evaluation metric selection
  • Result interpretation

Example prompts

  • "Help me formulate a hypothesis for testing the effectiveness of this new sorting algorithm."
  • "Summarize the key findings from these five papers on reinforcement learning."
  • “What are appropriate metrics to evaluate the performance of a recommendation system?”

Tips & gotchas

The skill’s output is based on established computer science research practices; familiarity with basic research concepts will improve results. While it can offer guidance, it's not a substitute for expert domain knowledge or critical thinking.