asiai AGENTS.md

asiai AGENTS.md is an instructions file for Codex, OpenCode from druide67/asiai. It costs 1,613 tokens per session, scanned B, original, Apache-2.0.

Project-specific instructions for asiai, a Python command-line tool that manages, benchmarks, and monitors local language models on Apple Silicon Macs.

In plain words
What is it for?
Use them when modifying asiai, diagnosing its installation or monitoring tools, or working with its supported local model engines.
Why use it?
They give coding agents the project's structure, supported systems, architecture, and development conventions before they change code.

Instructions file for CodexOpenCode

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 instructions/druide67/asiai/agents-md
Clone the repo
git clone --depth 1 https://github.com/druide67/asiai

Made for: Codex, OpenCode.

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 asiai AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/druide67/asiai/agents-md.svg)](https://agentmods.dev/instructions/druide67/asiai/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/druide67/asiai/agents-md"><img src="https://agentmods.dev/badge/instructions/druide67/asiai/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,613 This file is loaded in full into every session.
When invoked 1,613 The same file — it is already loaded in full.
Security scan B 1 finding. 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 $0.01613 $0.01613
Opus 5 $0.00807 $0.00807
Sonnet 5 $0.00323 $0.00323
Haiku 4.5 $0.00161 $0.00161

Measured 4d ago against content hash 564cc25cb18c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

asiai AGENTS.md scanned grade B with 1 finding 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.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

│ └── power.py # PowerMonitor (sudo powermetrics, GPU/CPU watts)
AGENTS.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — asiai

Guidelines for AI agents contributing to this project.

Project

asiai — open-source CLI to manage, benchmark, and monitor local LLM inference on Apple Silicon.

  • Language: Python 3.11+, zero external dependencies for the core (stdlib only)
  • Target: macOS Apple Silicon only (M1/M2/M3/M4). No Linux, no Windows.
  • License: Apache 2.0

Architecture

src/asiai/
├── cli.py              # CLI entry point (argparse)
├── doctor.py           # Installation and environment diagnostics
├── daemon.py           # launchd daemon management (continuous monitoring)
├── engines/            # Engine adapters (5 engines)
│   ├── base.py         # ABC InferenceEngine + dataclasses
│   ├── openai_compat.py # Base class for OpenAI-compatible engines (template method)
│   ├── detect.py       # Auto-detection (ports 11434, 1234, 8080, 8000)
│   ├── ollama.py       # Ollama adapter (native API)
│   ├── lmstudio.py     # LM Studio adapter (OpenAI-compatible)
│   ├── mlxlm.py        # mlx-lm adapter (OpenAI-compatible, Apple MLX native)
│   ├── llamacpp.py     # llama.cpp adapter (OpenAI-compatible, GGUF)
│   └── vllm_mlx.py     # vllm-mlx adapter (OpenAI-compatible, MLX)
├── collectors/         # Metric collectors (system, inference, power, macOS native)
│   └── power.py        # PowerMonitor (sudo powermetrics, GPU/CPU watts)
├── benchmark/          # Runner + standardized prompts + reporter + regression
│   └── regression.py   # Regression detection vs SQLite history
├── storage/            # SQLite (schema, migrations, dataclasses)
├── advisor/            # Hardware-aware recommendations
├── display/            # Renderers (CLI, TUI, Web)
│   ├── cli_renderer.py # CLI rendering (detect, bench, doctor, monitor)
│   ├── formatters.py   # Formatting helpers (ANSI, bytes, uptime)
│   ├── tui.py          # Textual dashboard (optional)
│   └── tui.tcss        # Textual styles
└── web/                # Web dashboard (optional: pip install asiai[web])
    ├── app.py          # FastAPI factory + lifespan + Jinja2
    ├── state.py        # AppState + BenchStatus dataclasses
    ├── routes/         # Route handlers (dashboard, bench, monitor, history, doctor)
    ├── templates/      # Jinja2 templates + partials
    └── static/         # CSS + JS (ApexCharts config)

Read the full file on GitHub · 137 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 · 137 lines · 1,613 tokens per session scan B 564cc25cb18c

Subscribe to this mod's changes

asiai AGENTS.md is an instructions file published in the GitHub repository druide67/asiai (11 stars, last pushed 5d ago), licensed Apache-2.0. It adds 1,613 tokens to every session, about $0.0081 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.