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Chat Ui

Checked
inference-sh·vlatest·frontend

Provides a chat interface for running inference jobs via shell commands, simplifying complex AI 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 inference-sh/skills --skill chat-ui -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

inference-sh

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 inference-sh/skills at c2d5678f14.

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

Commit
c2d5678f14
Manifest
ui/chat-ui/SKILL.md
Scanned
1 file, 127 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 chat-ui skill provides a standardized interface for AI agents to handle conversational interactions, enabling them to process and generate natural language responses effectively. It serves as the foundational layer for building responsive dialogue systems within the inference-sh ecosystem.

When to use it

  • Implementing real-time customer support bots that require immediate text-based replies.
  • Developing internal knowledge base assistants for querying company documentation.
  • Creating interactive tutorials where agents guide users through step-by-step processes via chat.
  • Building conversational interfaces for data analysis tools to explain complex results naturally.

Key capabilities

  • Manages natural language input and output streams between the user and the AI model.
  • Facilitates structured dialogue sessions with consistent formatting.
  • Integrates seamlessly with inference-sh backend services for processing requests.

Example prompts

  • "Explain how to reset my password in three simple steps."
  • "What are the top five features of our latest product update?"
  • "Help me draft a follow-up email based on this meeting summary."

Tips & gotchas

Ensure your backend inference endpoints are properly configured before activating the chat interface, as the UI relies entirely on successful model responses. Limit session timeouts to prevent users from waiting indefinitely if the AI is processing complex queries.