auto-draw-plot

auto-draw-plot is a skill for Claude Code, Codex from huangwb8/skills. It costs 108 tokens per session (5,287 once invoked), scanned B, original, MIT.

A workflow for planning and creating images from a written description. It supports general images as well as roadmaps, flowcharts, schematics, and architecture diagrams.

In plain words
What is it for?
Use it to turn ideas into generated images, technical diagrams, or revised image versions, with visual checks between iterations.
Why use it?
It removes the need to design image prompts and manage repeated image edits by hand.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads ~/.codex paths; mentions Codex.

Good fit Use it to turn ideas into generated images, technical diagrams, or revised image versions, with visual checks between iterations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/huangwb8/skills/auto-draw-plot
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.

Any agent
npx skills add huangwb8/skills --skill auto-draw-plot
Clone the repo
git clone --depth 1 https://github.com/huangwb8/skills

Made for: Claude Code, Codex.

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 auto-draw-plot

README.md
[![agentmods](https://agentmods.dev/badge/skills/huangwb8/skills/auto-draw-plot/github.svg)](https://agentmods.dev/skills/huangwb8/skills/auto-draw-plot)
Your own site
<a href="https://agentmods.dev/skills/huangwb8/skills/auto-draw-plot"><img src="https://agentmods.dev/badge/skills/huangwb8/skills/auto-draw-plot/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.

agentmods 80×15 button for auto-draw-plot

Your own site · 80×15
<a href="https://agentmods.dev/skills/huangwb8/skills/auto-draw-plot"><img src="https://agentmods.dev/badge/skills/huangwb8/skills/auto-draw-plot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 108 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,287 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00108 $0.05287
Opus 5.5 $0.00043 $0.02115
Sonnet 5.5 $0.00022 $0.01057
Haiku 4.5 $0.00011 $0.00529

Measured 1mo ago against content hash 7db5bc4416d9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

auto-draw-plot 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 1mo ago.

The scan reads SKILL.md. This mod also ships 12 executable files (scripts/build_parallel_plan.py, scripts/common.py, scripts/env_utils.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

- `api_config`(可选):Codex 本机配置优先使用 `~/.codex/config.toml` 中当前 BenszAPI provider 的 `base_url` 与 `experimental_bearer_token`;`~/.codex/auth.json` 仅作为兼容认证来源,`~/.bensz-skills/config/remote.env` 只作为缺失字段的兜底。默认 `auto` 只在运行前按优先级选
skills/alpha/auto-draw-plot/SKILL.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auto Draw Plot

目标

  • 以用户需求为起点,由宿主 AI 进行语义规划,再构造适用于当前图片 provider 的 prompt,通过 BenszAPI 直接完成“parallel-vibe 规划留痕 → prompt → 出图 → 视觉评估 → 继续/停止”的闭环;脚本默认不调用额外 Gemini 文本接口。
  • 触发边界:默认模式是 general;用户明确要技术路线图/roadmap/flowchart 时使用 roadmap,明确要原理图/机制图/架构图时使用 schematic。后续新增类型应作为 config.yaml:modes.presets 扩展,不改主流程。
  • parallel-vibe 是必选工作流的一部分,不是可选增强;默认通过 scripts/run_draw_plot.py 在独立隐藏工作区里完成整个闭环。
  • auto-draw-plot 独立负责需求拆解、prompt 生成、图片 generation/edit、多轮保真微调、评估与交付;图片请求由本 skill 的脚本通过 BenszAPI 提交,不调用也不依赖 imagegen skill。完整的 imagegen 技能边界见「Skill 专属约束」。

流程

输入

  • user_need(必需):自然语言描述的图像需求、输出用途、必要的视觉语义与格式要求。
  • mode(可选):general / roadmap / schematic;默认 general。模式只改变 prompt preset、默认画布和评估口径,不引入 legacy draw.io 渲染器。三种模式的语义与文字策略:
    • general:通用绘图模式,适合普通信息图、封面图、概念图和自由描述。
    • roadmap:技术路线图模式,强调 3-5 阶段、阶段标题条、主链箭头、风险/备选虚线、A4 打印可读。
    • schematic:原理图/机制图模式,强调分组大框、圆角节点、机制链/模块关系、主链与辅助箭头分层。
    • roadmap / schematic 的文字策略:优先把标签自然换成 2-3 行,也不要横向压缩字形;默认使用现代黑体/思源黑体/Noto Sans CJK 风格的正常字宽、常规到半粗体。除非用户明确要求窄体标题或压缩排版,否则禁止窄体、长体、压缩体、condensed/narrow/compressed font、横向压缩和瘦长拉伸字体。
    • 不要把 roadmap / schematic 回退成 draw.io、SVG/PDF 或 TEX 强绑定流程;这些 legacy 能力只作为 prompt 和评估经验迁移。
  • api_config(可选):Codex 本机配置优先使用 ~/.codex/config.toml 中当前 BenszAPI provider 的 base_url 与 experimental_bearer_token;~/.codex/auth.json 仅作为兼容认证来源,~/.bensz-skills/config/remote.env 只作为缺失字段的兜底。默认 auto 只在运行前按优先级选择连接与鉴权检查通过的 provider,真实生成资格以 Images submit 响应为准。
  • image_provider(可选):用户明确指定的图片模型/provider,如 gpt-image-2.5-flare、gpt-image-2.5-sunburst、gpt-image-2 或 nano_banana。显式指定后必须只用该 provider/model,失败时暂停并报告原因,不得切换到其他模型。
  • allow_provider_fallback(可选):只有用户明确说“失败可以换模型/可以回退到另一个 provider”时才为 true;该授权仅覆盖已确认未创建任务的 provider 故障,不覆盖订阅、余额、权限、overage、计费服务错误或 submit 空/非 JSON 等任务创建状态不确定的协议错误。
  • max_rounds(可选):最大优化轮数,默认 3;若用户另有指定,以用户为准。
  • visual_constraints(可选):比例、期望布局、色调、字体等硬约束。尺寸只作为 provider 原生尺寸选择参考,不承诺最终导出像素。
  • quality / provider_size / output_format / output_compression(可选):OpenAI 图片模型显式 provider 参数;默认模型为 gpt-image-2.5-flare,默认参数分别为 low、1024x1024、jpeg、85,均执行白名单或范围校验。
  • reference_images(可选):用于 prompt 引导的风格/布局图;第 2 轮起上一轮 output.jpg 会自动作为第一参考图,用户参考图排在其后。
  • workspace_base(可选):用户显式指定的隐藏工作区根目录;未指定时使用当前目录 .bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/auto-draw-plot/。

Read the full file on GitHub · 130 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. 1mo ago Changed · +21 tokens per session 7db5bc4416d9
  2. 1mo ago Changed · -20 lines a9ca62e54b1f
  3. 1mo ago Changed · +30 lines 094267b79bd5
  4. 1mo ago First seen · 120 lines · 87 tokens per session scan B 8f6feef871fe

Subscribe to this mod's changes

auto-draw-plot is a skill published in the GitHub repository huangwb8/skills (50 stars, last pushed 10d ago), licensed MIT. It adds 108 tokens to every session and 5,287 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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