packages/skills/skills/tools-ui/SKILL.md
--- name: tools-ui description: "Tool lifecycle UI components for React/Next.js from ui.inference.sh. Display tool calls: pending, progress, approval required, results. Capabilities: tool status, progress indicators, approval flows, results display. Use for: showing agent tool calls, human-in-the-loop approvals, tool output. Triggers: tool ui, tool calls, tool status, tool approval, tool results," agent tools, mcp tools ui, function calling ui, tool lifecycle, tool pending --- # Tool UI Compon
npx skillsauth add mediar-ai/skillhubz packages/skills/skills/tools-uiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Tool lifecycle components from ui.inference.sh.

npx shadcn@latest add https://ui.inference.sh/r/tools.json
| State | Description |
|-------|-------------|
| pending | Tool call requested, waiting to execute |
| running | Tool is currently executing |
| approval | Requires human approval before execution |
| success | Tool completed successfully |
| error | Tool execution failed |
import { ToolCall } from "@/registry/blocks/tools/tool-call"
<ToolCall
name="search_web"
args={{ query: "latest AI news" }}
status="running"
/>
import { ToolResult } from "@/registry/blocks/tools/tool-result"
<ToolResult
name="search_web"
result={{ results: [...] }}
status="success"
/>
import { ToolApproval } from "@/registry/blocks/tools/tool-approval"
<ToolApproval
name="send_email"
args={{ to: "[email protected]", subject: "Hello" }}
onApprove={() => executeTool()}
onDeny={() => cancelTool()}
/>
import { ToolCall, ToolResult, ToolApproval } from "@/registry/blocks/tools"
function ToolDisplay({ tool }) {
if (tool.status === 'approval') {
return (
<ToolApproval
name={tool.name}
args={tool.args}
onApprove={tool.approve}
onDeny={tool.deny}
/>
)
}
if (tool.result) {
return (
<ToolResult
name={tool.name}
result={tool.result}
status={tool.status}
/>
)
}
return (
<ToolCall
name={tool.name}
args={tool.args}
status={tool.status}
/>
)
}
<ToolCall
name="read_file"
args={{ path: "/src/index.ts" }}
status="running"
className="border-blue-500"
/>
Tools automatically get icons based on their name:
| Pattern | Icon |
|---------|------|
| search*, find* | Search |
| read*, get* | File |
| write*, create* | Pencil |
| delete*, remove* | Trash |
| send*, email* | Mail |
| Default | Wrench |
The Agent component handles tool lifecycle automatically:
import { Agent } from "@/registry/blocks/agent/agent"
<Agent
proxyUrl="/api/inference/proxy"
config={{
core_app: { ref: 'openrouter/claude-sonnet-45@0fkg6xwb' },
tools: [
{
name: 'search_web',
description: 'Search the web',
parameters: { query: { type: 'string' } },
requiresApproval: true, // Enable approval flow
},
],
}}
/>
# Full agent component (recommended)
npx skills add inference-sh/skills@agent-ui
# Chat UI blocks
npx skills add inference-sh/skills@chat-ui
# Widgets for tool results
npx skills add inference-sh/skills@widgets-ui
Component docs: ui.inference.sh/blocks/tools
tools
Use when the user wants to manage Valet agents, channels, connectors, organizations, or environment variables (secrets and plain config) via the valet CLI. Handles creation, deployment, linking, teardown, and all multi-step workflows. Also use when asked to "create an agent", "deploy an agent", "design an agent", "build me an agent that...", "create a connector", "set up a webhook", or anything involving the Valet platform or any request to create and deploy AI agents. Also use when asked to "learn from this session", "capture this workflow", "save this as an agent", "make this repeatable", or when writing SOUL.md files.
tools
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testing
# Faceless.so Turn a script, prompt, Reddit post, or blog into a Remotion short with TTS, captions, and B-roll, then auto-post to YouTube, TikTok, Instagram, X, Facebook, LinkedIn, and Threads. ## Prerequisites - A Faceless.so account (from $24/mo) at https://faceless.so - Source material: script, prompt, Reddit URL, or blog URL - Destination social accounts to auto-post (YouTube, TikTok, Instagram, X, Facebook, LinkedIn, Threads) ## Instructions 1. Open https://faceless.so and start a new
testing
# BIMI SVG Tiny P/S Corpus Validator Use the public makeBIMI SVG Tiny P/S Test Corpus to evaluate an SVG against its evidence-bound fixture rules and to report the result clearly. ## Inputs Accept either an SVG file, an SVG URL, or raw SVG markup. If the source cannot be retrieved or parsed as XML, stop and report that limitation. ## Authoritative corpus 1. Retrieve the current manifest from `https://makebimi.com/public/test-corpus/v1/manifest.json`. 2. Record `schema_version`, `corpus_vers