detect.it

detect.it is a command for coding agents from druide67/asiai. It costs 38 tokens per session (667 once invoked), scanned A, original, Apache-2.0.

A Mac command that finds locally running large-language-model inference engines, which are programs that run AI models.

In plain words
What is it for?
It detects engines through saved configuration, port scans, or process checks, and can scan specific URLs.
Why use it?
It saves you from checking configuration files, network ports, and running processes manually to find available engines.

Command

Install

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.

agentmods
npx agentmods add commands/druide67/asiai/detect.it
Clone the repo
git clone --depth 1 https://github.com/druide67/asiai

Wrote 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.

agentmods badge for detect.it

README.md
[![agentmods](https://agentmods.dev/badge/commands/druide67/asiai/detect.it.svg)](https://agentmods.dev/commands/druide67/asiai/detect.it)
Your own site
<a href="https://agentmods.dev/commands/druide67/asiai/detect.it"><img src="https://agentmods.dev/badge/commands/druide67/asiai/detect.it.svg" alt="Measured on agentmods" height="20"></a>
Per session 38 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 667 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00038 $0.00667
Opus 5 $0.00019 $0.00333
Sonnet 5 $0.00008 $0.00133
Haiku 4.5 $0.00004 $0.00067

Measured 4d ago against content hash 9c44f647825d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

detect.it 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 4d 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.

docs/commands/detect.it.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

asiai detect

Rilevamento automatico dei motori di inferenza con cascata a 3 livelli.

Uso

asiai detect                      # Rilevamento automatico (cascata a 3 livelli)
asiai detect --url http://host:port  # Scansiona solo URL specifici

Output

Detected engines:

  ● ollama 0.17.4
    URL: http://localhost:11434

  ● lmstudio 0.4.5
    URL: http://localhost:1234
    Running: 1 model(s)
      - qwen3.5-35b-a3b  MLX

  ● omlx 0.9.2
    URL: http://localhost:8800

Come funziona: rilevamento a 3 livelli

asiai utilizza una cascata di tre livelli di rilevamento, dal più veloce al più approfondito:

Livello 1: Configurazione (più veloce, ~100ms)

Legge ~/.config/asiai/engines.json — motori scoperti nelle esecuzioni precedenti. Questo rileva motori su porte non standard (es. oMLX su 8800) senza dover riscansionare.

Livello 2: Scansione porte (~200ms)

Scansiona le porte predefinite più un range esteso:

Porta Motore
11434 Ollama
1234 LM Studio
8080 mlx-lm o llama.cpp
8000-8009 oMLX o vllm-mlx
52415 Exo

Livello 3: Rilevamento processi (fallback)

Usa ps e lsof per trovare processi motore in ascolto su qualsiasi porta. Rileva motori in esecuzione su porte completamente inaspettate.

Persistenza automatica

Qualsiasi motore scoperto al Livello 2 o 3 viene automaticamente salvato nel file di configurazione (Livello 1) per un rilevamento più rapido la volta successiva. Le entry autodiscoverte vengono eliminate dopo 7 giorni di inattività.

Quando più motori condividono una porta (es. mlx-lm e llama.cpp su 8080), asiai usa il probing degli endpoint API per identificare il motore corretto.

URL espliciti

Usando --url, vengono scansionati solo gli URL specificati. Nessuna configurazione viene letta o scritta — utile per controlli una tantum.

asiai detect --url http://192.0.2.10:11434,http://localhost:8800

Vedi anche

  • config — Gestire la configurazione persistente dei motori

Read the full file on GitHub · 74 lines

Changes

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.

  1. 4d ago First seen · 74 lines · 38 tokens per session scan A 9c44f647825d

Subscribe to this mod's changes

detect.it is a command published in the GitHub repository druide67/asiai (11 stars, last pushed 5d ago), licensed Apache-2.0. It adds 38 tokens to every session and 667 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 2026-08-30.