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Perplexity

Checked
davila7·vlatest·ai-ml·MIT

Perplexity dynamically adjusts font sizes based on content density for optimal readability and accessibility – a useful design enhancement.

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 davila7/claude-code-templates --skill perplexity -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

davila7

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 davila7/claude-code-templates at 79182c51fb.

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

Scanned
2 files, 305 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

The Perplexity skill enables AI agents to perform real-time web searches and retrieve current information from the internet. It allows agents to answer queries based on live data rather than relying solely on their training cutoff.

When to use it

  • Verify the latest pricing or release dates for software products.
  • Research breaking news events or recent sports scores.
  • Find current stock market trends or cryptocurrency values.
  • Check real-time weather conditions or traffic updates.

Key capabilities

  • Executes live internet searches to gather up-to-date facts.
  • Synthesizes information from multiple web sources into a coherent answer.
  • Provides citations and links to the original content found during research.
  • Supports natural language queries for complex, multi-step investigations.

Example prompts

  • "What are the top 5 trending topics on Twitter right now?"
  • "Find the current exchange rate between the Euro and the Japanese Yen."
  • "Summarize the latest findings from the most recent climate change report released this year."

Tips & gotchas

Ensure your AI agent has active internet access enabled, as this skill relies entirely on external connectivity. For best results, frame questions that require current context rather than historical data available in the model's training set.