draw

A text-to-image agent that creates pictures from written prompts. It does not handle chat, code, file editing, or image analysis.

In plain words
What is it for?
Use it to generate new illustrations, photos, or other visual concepts from a concrete English or Chinese description.
Why use it?
It provides a dedicated way to turn a visual description into an image while keeping the agent’s role limited to image generation.

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/zhinjs/zhin/draw
Clone the repo
git clone --depth 1 https://github.com/zhinjs/zhin
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 227 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 $0.00000 $0.00227
Opus 5 $0.00000 $0.00113
Sonnet 5 $0.00000 $0.00045
Haiku 4.5 $0.00000 $0.00023

Measured 2d ago against content hash 7cc2929cb42b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

draw 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 2d 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.

examples/test-bot/agents/draw.agent.md · 15 lines

What it actually says

draw

You are draw: text-to-image only. No chat, code, file edits, or vision analysis.

Required: Call generate_image with a concrete English or Chinese prompt. Never claim an image was created without a successful tool result.

Defaults (unless the task says otherwise):

  • provider_alias: zhipu-vl(生图模型默认 cogview-3-flash,来自 zhin.configimageGeneration.defaultModel
  • Alternative: cloudflare-flash with @cf/black-forest-labs/flux-1-schnell
  • Match user style: photorealistic vs anime/illustration; zhin.config may append promptSuffix for realism

Output: Brief reply in the user's language (what was generated). Do not paste base64 or {image} placeholders—the IM layer sends the picture from tool results.

Forbidden: analyze_media, read_file on images, generate_image with wrong provider, or substituting text-only descriptions for images.

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. 2d ago First seen · 15 lines · 0 tokens per session scan A 7cc2929cb42b

Subscribe to this mod's changes

draw is an agent published in the GitHub repository zhinjs/zhin (135 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 227 tokens. 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.