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Agent Ui

Checked
inference-sh·vlatest·agents

Dynamically generates user interfaces based on inference results, enabling interactive data exploration and decision support.

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 agent-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/agent-ui/SKILL.md
Scanned
1 file, 111 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

This skill, Agent Ui, dynamically generates user interfaces based on inference results from AI agents. It allows for interactive data exploration and decision support by providing a runtime environment with built-in tool lifecycle management (pending, progress, approval, results) and human-in-the-loop approval flows. The UI is driven by declarative JSON responses from the agent, enabling flexible widget creation and real-time token streaming.

When to use it

  • When you need a user interface for interacting with an AI agent's output in a structured way.
  • For applications requiring human review or approval of agent actions.
  • To build interfaces that display data generated by the agent, such as forms or visualizations.
  • In scenarios where real-time updates and streaming responses are important.
  • When you want to incorporate client-side tools into your agent workflows.

Key capabilities

  • Runtime Included: No backend logic is required for the UI component.
  • Tool Lifecycle Management: Tracks tool status (pending, progress, approval, results).
  • Human-in-the-Loop Approval Flows: Built-in support for human review and approval of agent actions.
  • Declarative JSON UI: Generates UIs from agent responses in JSON format.
  • Streaming: Provides real-time token streaming.
  • Client-Side Tools: Supports tools that run directly within the browser.

Example prompts

These are not prompts to the skill, but configurations for an agent using the skill:

  • proxyUrl = "/api/inference/proxy" (required to connect)
  • agentConfig.core_app.ref = 'openrouter/claude-haiku-45@0fkg6xwb' (specifies a core AI model)
  • agentConfig.system_prompt = 'You are helpful.' (sets the agent's persona)

Tips & gotchas

  • API Proxy Required: This skill requires an API proxy route setup as described in the documentation (/api/inference/proxy).
  • Environment Variable: Ensure you have set the INFERENCE_API_KEY environment variable.
  • Client-Side Tools: To utilize client-side tools, use the createScopedTools function and pass it to the agent's configuration.