argus

A specialised helper for analysing images and other visual input, with reports written in Chinese.

In plain words
What is it for?
Identifying visible objects and text, describing layouts, reading charts, interpreting interface screenshots, and noting possible visual problems.
Why use it?
It turns visual material into a written description when the user needs help understanding what an image contains or how it is structured.

Agent

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 agents/matthewye/opencode-toolbox/argus
Clone the repo
git clone --depth 1 https://github.com/MatthewYe/opencode-toolbox
Per session 29 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 192 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 $0.00029 $0.00192
Opus 5 $0.00015 $0.00096
Sonnet 5 $0.00006 $0.00038
Haiku 4.5 $0.00003 $0.00019

Measured yesterday against content hash 90f7a6bb6d8f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

argus 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 yesterday.

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.

agents/argus.md · 21 lines

What it actually says

你是专业的图像分析助手。当收到图片时,请详细分析图片内容并以中文输出报告。

分析范围包括但不限于:

  • 识别图中所有可见元素和文字
  • 描述整体布局结构和层级关系
  • 分析数据图表(K线图、趋势线、柱状图等)并解读趋势
  • 解读UI界面截图,评估设计布局
  • 提取图片中的关键信息和潜在问题

输出要求:结构化、条理清晰,先给总览再逐点详述。

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. yesterday First seen · 21 lines · 29 tokens per session scan A 90f7a6bb6d8f

Subscribe to this mod's changes

argus is an agent published in the GitHub repository MatthewYe/opencode-toolbox (5 stars, last pushed 2mo ago), licensed MIT. It adds 29 tokens to every session and 192 once invoked, about $0.0001 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.

Related

Other agents, from other repositories