Skip to content
TrustedSkillsbeta
Back to all skills

Minimax Web Search

Listed
thincher·vlatest·backend

Helps with web development, search as part of developing backend services and APIs workflows.

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 thincher/awsome_skills --skill minimax-web-search -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

thincher

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 failed 2 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: api.minimaxi.com, astral.sh.

    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.

    Hosts contacted

    astral.shundeclaredapi.minimaxi.comundeclared

    What it found (3 of 4)

    • minimax-web-search/SKILL.md:24contacts astral.sh
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • minimax-web-search/SKILL.md:32contacts astral.sh
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • minimax-web-search/SKILL.md:38contacts astral.sh
      curl -LsSf https://astral.sh/uv/install.sh | sh

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 3 places.

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

    What it found

    • minimax-web-search/SKILL.md:24remote script piped into a shell
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • minimax-web-search/SKILL.md:32remote script piped into a shell
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • minimax-web-search/SKILL.md:38remote script piped into a shell
      curl -LsSf https://astral.sh/uv/install.sh | sh

  • 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 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.

  • Pinned to a commit: passed

    Scanned thincher/awsome_skills at fe166efc4b.

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

Commit
fe166efc4b
Manifest
minimax-web-search/SKILL.md
Scanned
3 files, 236 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

The thincher-minimax-web-search skill enables AI agents to perform web searches and retrieve relevant information. It leverages a minimax strategy to optimize search results, aiming for both breadth and depth in its findings. The agent can then use these extracted details for various tasks like answering questions or summarizing topics.

When to use it

  • Researching a topic: When an AI needs to gather background information on a subject before generating content or making decisions.
  • Answering factual questions: To provide accurate and up-to-date answers based on current web data.
  • Summarizing news events: Quickly compile key details from multiple online sources about recent happenings.
  • Competitive analysis: Gathering information about competitors, products, or market trends from publicly available websites.

Key capabilities

  • Minimax search strategy for optimized results
  • Web search functionality
  • Information retrieval
  • Data extraction

Example prompts

  • "Find the latest news on electric vehicle charging infrastructure."
  • "What are the key features of the new iPhone?"
  • "Summarize recent developments in AI regulation."

Tips & gotchas

The quality of results depends heavily on the clarity and specificity of the search query. Broad or ambiguous prompts may return less relevant information.