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Agent Skill · 研究检索

figure-designer(人物设计师)

figure-designer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

figure-designer 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 71,089。

总安装 196周安装 8GitHub Stars 484下载 63核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:figure-designer(人物设计师)
来源仓库:https://github.com/hkustdial/supervisor-skills
仓库路径:skills/figure-designer
安装命令:
npx skills add https://github.com/hkustdial/supervisor-skills --skill figure-designer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/hkustdial/supervisor-skills --skill figure-designer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

figure-designer 用于查找、检索和筛选相关信息,适合快速定位候选结果。可在 Codex、Claude、Cursor、Gemini CLI 中结合关键词或任务场景使用。建议参考来源仓库和 README 核验具体用法和功能细节。

安装方式:github,命令为 npx skills add https://github.com/hkustdial/supervisor-skills --skill figure-designer。注意:安装前应确认权限范围和维护状态,避免触发未授权的联网或文件操作。

来源仓库内路径:skills/figure-designer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/hkustdial/supervisor-skills --skill figure-des…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

figure-designer 怎么安装?

在终端执行 npx skills add https://github.com/hkustdial/supervisor-skills --skill figure-designer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

figure-designer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

figure-designer 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

figure-designer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

figure-designer 用的人多吗?

公开数据是累计安装 196 次,近一周安装 8 次,下载 63 次,GitHub 484 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

figure-designer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
figure-designer

人物设计师 · 本页

196484只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Figure Designer

Overview

A top-venue paper typically carries six to eight figures, with three carrying almost all the storytelling weight: the Motivated Example (Figure 1, on page 1 or the top of page 2), the Solution Overview (inside the Methodology section), and the Experimental Results figures (inside the Experiments section). Reviewers scan these three in under a minute to decide whether the paper is worth reading in detail; weak figures sink otherwise-strong papers.

This skill takes the user's intent (what they want to communicate) plus context (research area, method name, target venue) and returns the recommended paradigm, a layout sketch, labelling guidance, tool suggestion, and a quality-control audit against a universal rule set (vector format, font size, colour-blind-safe encoding, self-contained caption, honest axis ranges).

When to use this skill

  • Before drawing any figure in a paper.
  • The user asks to 'design a figure', 'draw Figure 1', 'plot experiment results', 'choose the right chart type'.
  • The user has drawn a figure and wants a design audit.
  • The user is unsure which figure type or paradigm to choose.
  • Preparing camera-ready figures before submission.

When NOT to use this skill

  • The user only wants generic plotting help (bar chart, line chart) outside a paper. Regular assistance suffices.
  • The paper is not yet structured; use intro-drafter or tech-paper-template first to decide what figures the paper needs.
  • The user wants a review of an already-finished paper. Use pre-submission-reviewer.

Core procedure

Step 1: Figure-type identification

Decide which of the three core types the figure is. If the user's request does not match any, either it is a supporting figure (use the experimental-results guidance as a base) or it does not belong in the paper.

If the mode is figure-audit and the user has provided an image path, load the image with the Read tool before proceeding to Step 2. Vision-based inspection enables the universal rule audit in Step 6 to check font legibility, colour palette, raster-vs- vector tells, and chartjunk directly rather than relying on user description. If no image is provided, continue in text-only mode and mark vision-only rules (font size, raster detection, colour palette) as "user must verify" in the final audit report.

Step 2: Paradigm recommendation

See: references/motivated-example.md, references/solution-overview.md, or references/experimental-results.md depending on figure type.

Each figure type has two to three canonical paradigms. Pick the one that fits the user's storytelling need, and explain why the other paradigms fit less well.

Step 3: Layout sketch

Produce a text description of the layout: panel positions, element placement, arrows, colour assignments. The goal is that the user could draw the first draft from the sketch alone.

Step 4: Labelling and annotation guidance

  • Name every visible element concretely (no "Module A", "X", "Y").
  • Annotate critical points (failure highlight, success highlight, comparison emphasis).
  • Specify font sizes and colour palette. Default colour palette: ColorBrewer Qualitative or Viridis for sequential.

Step 5: Tool suggestion

See: references/tools.md for the tool matrix and the decision heuristic.

Default recommendations:

  • Motivated Example and Solution Overview: PowerPoint (draft), Figma (polish).
  • Experimental Results: Matplotlib or Seaborn in a reusable plot_utils.py script.
  • LaTeX-integrated figures: TikZ or PGFPlots.

Step 6: Universal rule audit

See: references/design-rules.md for the full universal rule set.

Verify every proposed or existing figure against:

  • Vector format (PDF, EPS, SVG) for export.
  • Font size at least 8pt post-scaling.
  • Small canvas (not large canvas with small fonts).
  • Colour-blind-safe palette; no colour-only encoding.
  • Self-contained caption whose first sentence states the core finding.
  • Honest axis ranges.
  • No 3D effects, no chartjunk.

Flag every violation with severity.

Step 7: Integrity gate

Run the checks in the Integrity gate section below.

Step 8: Output

Emit the full design in the Output format below.

Integrity gate

Bullets tagged [inspection] are checked by the LLM from its own output. Bullets tagged [user-verify] require the user to confirm because the check depends on either the drawn figure or knowledge the skill does not have (paper context, prior Introduction).

Before returning the design:

  1. [inspection] Paradigm matches figure type (motivated example is not a pipeline; overview is not a bar chart).
  2. [inspection] Layout sketch is concrete enough that the user could draw from it.
  3. [inspection] Labels are real entity names, not placeholders.
  4. [inspection] Tool suggestion matches the figure's complexity (not Matplotlib for a multi-icon motivated example, not PowerPoint for a 20-method bar chart).
  5. [inspection] when image provided, [user-verify] text-only Universal rule audit has been run; no CRITICAL violation is left unaddressed. Vision-only rules (raster-vs-vector, font size, colour palette) are only checkable when the user supplies an image.
  6. [user-verify] For motivated examples, the example is the same running example referenced by the Introduction (no new example introduced in Figure 1). The skill does not see the Introduction; the user confirms.
  7. [inspection] For experimental results, the chart type matches the data type (time-series uses line, multi-method comparison uses grouped bar, trade-off uses scatter).

If any [inspection] check fails, mark the design as "needs user attention". For [user-verify] items, surface them to the user as items they must confirm before submission.

Output format

1. Figure type

  • Type:
  • Reason:

2. Paradigm recommendation

  • Paradigm:
  • Why this paradigm:
  • Alternatives considered and rejected:

3. Layout sketch

  • Canvas:
  • Panels:
  • Arrows and connections:
  • Colour assignment:

4. Labelling and annotations

  • Element names:
  • Critical highlights:
  • Font sizes:
  • Colour palette:

5. Tool suggestion

  • Primary:
  • Alternative:
  • Reason:

6. Universal rule audit

  • Vector format:
  • Font size:
  • Colour-blind safe:
  • Self-contained caption:
  • Honest axis range (if applicable):
  • No chartjunk:

7. Integrity gate result

  • Gate 1-7:

8. Severity summary

  • CRITICAL, MAJOR, MINOR
  • Top three actions first:...

平台分布

Codex

38.5%
按下载量换算24

Claude

29.24%
按下载量换算18

Cursor

20.14%
按下载量换算13

Gemini CLI

8.89%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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