Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Ampli-Group/agentic-mobile-blueprintnpx agentmods add skills/ampli-group/agentic-mobile-blueprint/langfuse-tracingWrote 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/ampli-group/agentic-mobile-blueprint/langfuse-tracing)<a href="https://agentmods.dev/skills/ampli-group/agentic-mobile-blueprint/langfuse-tracing"><img src="https://agentmods.dev/badge/skills/ampli-group/agentic-mobile-blueprint/langfuse-tracing/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/ampli-group/agentic-mobile-blueprint/langfuse-tracing"><img src="https://agentmods.dev/badge/skills/ampli-group/agentic-mobile-blueprint/langfuse-tracing.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 | $0.00041 | $0.00868 |
| Opus 5 | $0.00020 | $0.00434 |
| Sonnet 5 | $0.00008 | $0.00174 |
| Haiku 4.5 | $0.00004 | $0.00087 |
Grade A, and why
langfuse-tracing 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 10d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Langfuse Tracing for AI Operations
Available Modules
_shared/langfuse/
├── shared.ts # Base: Tracer, withTrace()
├── gemini.ts # Gemini: text, tools, images
├── anthropic.ts # Anthropic: Claude text, tools
└── openai.ts # OpenAI: text, tools, images
Basic Usage
Wrap Function with Tracing
import { withTrace, traceLLMGemini } from '../_shared/langfuse/gemini.ts';
Deno.serve(async (req: Request) => {
return await withTrace(
{
name: 'my-function',
userId: user.id,
sessionId: item_id,
input: { prompt: 'analyze this' },
metadata: { function: 'my-function' },
tags: ['ai', 'analysis'],
},
async (tracer) => {
// Your AI calls here
const { text } = await traceLLMGemini(tracer, {
model: 'gemini-2.5-flash',
messages: [{ role: 'user', content: 'Hello' }],
});
return new Response(JSON.stringify({ result: text }));
}
);
});
Gemini: Text Completion
const { text, usage } = await traceLLMGemini(tracer, {
model: 'gemini-2.5-flash',
messages: [{ role: 'user', content: 'Summarize this' }],
temperature: 0.7,
maxTokens: 500,
});
Gemini: Structured Output
const { data } = await traceLLMGemini<{ title: string; price: number }>(tracer, {
model: 'gemini-2.5-flash',
messages: [{ role: 'user', content: 'Extract product info' }],
schema: {
type: 'object',
properties: {
title: { type: 'string' },
price: { type: 'number' },
},
required: ['title', 'price'],
},
});
// data.title, data.price are typed!
Gemini: Function Calling
const result = await traceLLMWithToolsGemini(tracer, 'agent-name', {
model: 'gemini-2.5-flash',
messages: [{ role: 'user', content: 'Get weather in SF' }],
tools: [{
name: 'get_weather',
description: 'Get current weather',
parameters: {
type: 'object',
properties: { location: { type: 'string' } },
required: ['location'],
},
}],
});
if (result.message.tool_calls) {
// Execute tools
}
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.
- 10d ago First seen · 123 lines · 41 tokens per session scan A d5c81dc80e68
langfuse-tracing is a skill published in the GitHub repository Ampli-Group/agentic-mobile-blueprint (4 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 868 once invoked, about $0.0002 per session on Opus 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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