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Qveris

Listed
hqman·vlatest·other

Qveris swiftly extracts key information from lengthy texts, boosting productivity by summarizing and highlighting crucial details instantly.

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 hqman/qveris --skill qveris -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

hqman

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: astral.sh, qveris.ai.

    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.shundeclaredqveris.aiundeclared

    What it found (3 of 4)

    • README.md:21contacts astral.sh
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • README.zh-CN.md:21contacts astral.sh
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • scripts/qveris_tool.py:26contacts qveris.ai
      BASE_URL = "https://qveris.ai/api/v1"

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 2 places.

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

    What it found

    • README.md:21remote script piped into a shell
      curl -LsSf https://astral.sh/uv/install.sh | sh
    • README.zh-CN.md:21remote 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 hqman/qveris at 1a09b3d97d.

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

Commit
1a09b3d97d
Manifest
SKILL.md
Scanned
5 files, 446 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 qveris skill allows AI agents to query and retrieve information from a database. It can perform searches based on keywords, filter results using specific criteria, and present the data in a structured format. This enables agents to access and utilize relevant knowledge for various tasks.

When to use it

  • Knowledge retrieval: An agent needs to quickly find answers to questions by searching a company's internal documentation.
  • Data filtering: An agent must identify specific products from a catalog based on criteria like price range, features, and availability.
  • Report generation: An agent is tasked with compiling data from multiple sources into a formatted report for stakeholders.
  • Inventory management: An agent needs to check stock levels of items in a warehouse.

Key capabilities

  • Database querying
  • Keyword searching
  • Data filtering based on criteria
  • Structured data presentation

Example prompts

  • "Find all products with a price between $50 and $100."
  • "Search the documentation for 'troubleshooting network connectivity'."
  • "Show me a list of customers who purchased product X in the last month."
  • “What is the current stock level of item Y?”

Tips & gotchas

The qveris skill requires access to and configuration with an existing database. Ensure the agent has appropriate permissions to query the specified database before use.