Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Prism-Shadow/agenthub --skill agenthub-typescriptgit clone --depth 1 https://github.com/Prism-Shadow/agenthubWrote 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/prism-shadow/agenthub/agenthub-typescript)<a href="https://agentmods.dev/skills/prism-shadow/agenthub/agenthub-typescript"><img src="https://agentmods.dev/badge/skills/prism-shadow/agenthub/agenthub-typescript/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/prism-shadow/agenthub/agenthub-typescript"><img src="https://agentmods.dev/badge/skills/prism-shadow/agenthub/agenthub-typescript.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00063 | $0.01139 |
| Opus 5.5 | $0.00025 | $0.00456 |
| Sonnet 5.5 | $0.00013 | $0.00228 |
| Haiku 4.5 | $0.00006 | $0.00114 |
Grade A, and why
agenthub-typescript 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentHub TypeScript
AgentHub is a unified SDK for calling LLMs across providers with shared data models, tool calling, tracing, and playground support.
Installation
npm install @prismshadow/agenthub
For model IDs, API keys, and base URLs, see Model selection.
Basic Usage
This example asks GPT to call a weather tool, runs the tool, then sends the result back.
import { AutoLLMClient } from "@prismshadow/agenthub";
function getWeather(location: string): string {
return `Temperature in ${location}: 22 C`;
}
// Map tool names to their implementations so calls can be dispatched by name.
const TOOLS: Record<string, (args: Record<string, any>) => string> = {
get_weather: (args) => getWeather(args.location as string),
};
async function main(): Promise<void> {
const weatherTool = {
name: "get_weather",
description: "Gets the current weather for a given location.",
parameters: {
type: "object" as const,
properties: {
location: {
type: "string" as const,
description: "The city name",
},
},
required: ["location"],
},
};
const client = new AutoLLMClient({ model: "gpt-5.5" });
const config = { tools: [weatherTool] };
let toolCall: { name: string; arguments: Record<string, any>; tool_call_id: string } | null = null;
for await (const event of client.streamingResponseStateful({
message: {
role: "user",
content_items: [{ type: "text", text: "What's the weather in London?" }],
},
config,
})) {
for (const item of event.content_items) {
if (item.type === "tool_call") {
toolCall = item; // collected as the stream arrives; no second pass
}
}
}
if (toolCall) {
// Dispatch by tool name instead of hardcoding the function.
const result = TOOLS[toolCall.name](toolCall.arguments);
for await (const event of client.streamingResponseStateful({
message: {
role: "user",
content_items: [
{
type: "tool_result",
text: result,
tool_call_id: toolCall.tool_call_id,
},
],
},
config,
})) {
console.log(event);
// Streams the final answer token by token, then a stop event carrying usage:
// { role: 'assistant', event_type: 'delta', content_items: [ { type: 'text', text: 'The' } ], usage_metadata: null, finish_reason: null }
// { role: 'assistant', event_type: 'delta', content_items: [ { type: 'text', text: ' weather' } ], usage_metadata: null, finish_reason: null }
// { role: 'assistant', event_type: 'delta', content_items: [ { type: 'text', text: ' is' } ], usage_metadata: null, finish_reason: null }
// { role: 'assistant', event_type: 'delta', content_items: [ { type: 'text', text: ' 22 C.' } ], usage_metadata: null, finish_reason: null }
// { role: 'assistant', event_type: 'stop', content_items: [], usage_metadata: { cached_tokens: 0, prompt_tokens: 12, thoughts_tokens: 0, response_tokens: 8 }, finish_reason: 'stop' }
}
}
}
void main();
What ships with it
4 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 · 115 lines · 63 tokens per session scan A 7355ca016cbb
agenthub-typescript is a skill published in the GitHub repository Prism-Shadow/agenthub (113 stars, last pushed 28d ago), licensed Apache-2.0. It adds 63 tokens to every session and 1,139 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 2026-08-30.
Other skills, from other repositories
android-expert
Expert in Android development with Jetpack Compose, Material Design, ViewModel, and modern Android architecture. Use when the user mentions mobile, Kotlin, Jetpack Compose, Material Design, or Google, or when the task involves Android Architecture, Android Components, Jetpack Libraries, or Activity/Fragment Lifecycle.
angular-expert
Expert knowledge in Angular framework, RxJS reactive programming, TypeScript, dependency injection, and enterprise application development. Use when the user mentions RxJS, TypeScript, dependency injection, reactive, frontend, or enterprise, or when the task involves Angular Fundamentals, RxJS Integration, Advanced…
nestjs-patterns
NestJS architecture patterns for modules, controllers, providers, DTO validation, guards, interceptors, config, and production-grade TypeScript backends.
bun-runtime
Bun as runtime, package manager, bundler, and test runner. When to choose Bun vs Node, migration notes, and Vercel support.
developing-genkit-js
Develop AI-powered applications using Genkit in Node.js/TypeScript. Use when the user asks about Genkit, AI agents, flows, or tools in JavaScript/TypeScript, or when encountering Genkit errors, validation issues, type errors, or API problems.
rubyllm
Build and maintain Ruby or Rails applications with the RubyLLM AI framework. Use for chats, agents, tools, MCP servers, structured output, judgments, evaluations, media generation, transcription, OCR, moderation, embeddings, reranking, tracing, Rails integration, and RubyLLM upgrades; not for contributing to the…