Borrowing it
Nothing to install: this file belongs to terrene-foundation/metis. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/terrene-foundation/metis/main/.claude/skills/20-interactive-widgets/SKILL.mdgit clone --depth 1 https://github.com/terrene-foundation/metisWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/terrene-foundation/metis/20-interactive-widgets)<a href="https://agentmods.dev/skills/terrene-foundation/metis/20-interactive-widgets"><img src="https://agentmods.dev/badge/skills/terrene-foundation/metis/20-interactive-widgets/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/terrene-foundation/metis/20-interactive-widgets"><img src="https://agentmods.dev/badge/skills/terrene-foundation/metis/20-interactive-widgets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.00921 |
| Opus 5.5 | $0.00029 | $0.00368 |
| Sonnet 5.5 | $0.00015 | $0.00184 |
| Haiku 4.5 | $0.00007 | $0.00092 |
Grade A, and why
interactive-widgets scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interactive Widget System
Production-ready patterns for building interactive widget systems that integrate with AI/LLM backends for dynamic, structured user interfaces.
Overview
Interactive widget patterns for:
- LLM-driven widget generation
- Streaming response with structured components
- Dynamic form builders
- Action-response patterns
- Widget protocol design
Reference Documentation
System Overview
- overview - Widget system architecture and navigation
- System components
- Documentation structure
- Quick reference
Technical Specification
- technical-spec - Complete technical specification
- Widget protocol design
- Backend integration
- Frontend rendering
- State management
- Error handling
Implementation Guide
- implementation-guide - Step-by-step implementation
- Backend widget generation
- Frontend widget rendering
- Event handling
- Real-world examples
Quick Patterns
Widget Protocol (JSON)
{
"type": "form",
"id": "user-input-form",
"content": {
"fields": [
{
"type": "text",
"name": "query",
"label": "Enter your question",
"required": true
}
],
"actions": [
{
"type": "submit",
"label": "Send",
"action": "submit_query"
}
]
}
}
Backend Widget Generation (Python)
def generate_widget_response(user_query: str) -> dict:
"""Generate structured widget response from LLM."""
response = llm.generate(
prompt=f"Generate a widget response for: {user_query}",
output_schema=WidgetSchema
)
return {
"type": response.widget_type,
"content": response.content,
"actions": response.available_actions
}
Frontend Widget Renderer (Dart)
Widget buildWidget(Map<String, dynamic> widgetData) {
switch (widgetData['type']) {
case 'form':
return FormWidget(data: widgetData['content']);
case 'card':
return CardWidget(data: widgetData['content']);
case 'table':
return TableWidget(data: widgetData['content']);
default:
return TextWidget(data: widgetData['content']);
}
}
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 142 lines · 73 tokens per session scan A ecfc4cd19ec2
interactive-widgets is a skill published in the GitHub repository terrene-foundation/metis (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 921 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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