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Llamaindex

Checked
davila7·vlatest·ai-ml·MIT

Quickly query and retrieve relevant information from your local documents using davila7's llamaindex integration.

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 davila7/claude-code-templates --skill llamaindex -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.

Commit
79182c51fb
Manifest
cli-tool/components/skills/ai-research/agents-llamaindex/SKILL.md
Scanned
4 files, 1,052 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 llamaindex skill enables AI agents to build and manage indexes for efficient querying of large datasets. It supports integration with various data sources, including documents, databases, and APIs, allowing for fast retrieval and analysis of information.

When to use it

  • When you need to create a searchable index from unstructured text or structured data.
  • To improve the performance of AI agents by enabling quick access to relevant information during conversations.
  • For applications requiring real-time querying of large volumes of data, such as customer support chatbots or knowledge management systems.

Key capabilities

  • Indexing and retrieval of documents and data sources
  • Integration with multiple data formats and APIs
  • Support for efficient query processing

Example prompts

  • "Create an index from the provided PDF documents to enable fast querying."
  • "Set up a database connection and build an index for real-time information retrieval."
  • "Optimize the search performance of my AI agent by using the llamaIndex skill."

Tips & gotchas

  • Ensure that your data sources are properly formatted and accessible before indexing.
  • Performance can vary depending on the size and complexity of the indexed data, so test with smaller datasets first.