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survey-visuals调查视觉效果

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

总安装

717

周安装

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GitHub Stars

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下载量

225
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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:survey-visuals(调查视觉效果)
来源仓库:https://github.com/willoscar/research-units-pipeline-skills
仓库路径:skills/survey-visuals
安装命令:
npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill survey-visuals
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill survey-visuals

简介

survey-visuals 用于辅助界面设计、视觉规范与交互体验优化。

  • 适合让 Agent 整理页面结构或生成 UI 方案。
  • 使用时需结合品牌与设计系统,避免仅堆装饰元素。survey-visuals 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 涉及真实页面改动时,应通过截图检查文本溢出与对齐。
  • 建议结合原始 README 核验具体功能与使用限制。

SKILL.md

Survey Visuals (timeline + figure specs; NO PROSE)

This skill creates non-prose artifacts that make the writing stage less template-y:

  • timeline / evolution bullets
  • figure specs (what to draw, why it matters, what papers support it)

Load Order

Always read:

  • references/overview.md
  • references/figure_archetypes.md

Read by task:

  • references/timeline_patterns.md when building timeline milestones

Machine-readable assets:

  • assets/figure_templates.yaml — figure archetype specifications (extensible without code changes)

Script Boundary

Use scripts/run.py only for:

  • deterministic assembly of timeline bullets from paper_notes + bibkeys
  • table generation from outline + mapping
  • figure spec skeleton generation using assets/figure_templates.yaml

Do not treat run.py as the place for:

  • hardcoded figure descriptions or narratives
  • milestone selection heuristics that should be inspectable from references

Tables are handled by dedicated table skills:

  • table-schema -> outline/table_schema.md
  • table-filler -> outline/tables_index.md (internal index)
  • appendix-table-writer -> outline/tables_appendix.md (reader-facing Appendix tables)

Inputs

  • outline/outline.yml
  • outline/claim_evidence_matrix.md
  • papers/paper_notes.jsonl
  • citations/ref.bib

Outputs

  • outline/timeline.md
  • outline/figures.md

Workflow inputs (explicit)

  • Use outline/outline.yml + outline/claim_evidence_matrix.md to decide what to visualize.
  • Use papers/paper_notes.jsonl for year/milestone candidates.
  • Use only citation keys from citations/ref.bib.

Workflow (heuristic)

  1. Read the outline + claim-evidence matrix and pick recurring comparison axes.
  2. Timeline (outline/timeline.md):

- Write year -> key milestone bullets (aim for breadth and citations).

  1. Figures (outline/figures.md):

- Write 2-4 figure specs that a human could draw: - purpose (what insight this figure communicates) - required elements (boxes/arrows/axes) - what papers support each element (cite keys)

  1. Use only citation keys present in citations/ref.bib.

Quality checklist

  • No TODO and no <!-- SCAFFOLD... --> markers remain in the outputs.
  • outline/timeline.md contains >=8 year bullets and each bullet has >=1 citation marker [@...].
  • outline/figures.md contains >=2 figure specs and each mentions at least one supporting citation.

Helper script (optional)

Quick Start

  • python.codex/skills/survey-visuals/scripts/run.py --help
  • python.codex/skills/survey-visuals/scripts/run.py --workspace <workspace_dir>

All Options

  • --workspace <workspace_dir> (required)
  • --unit-id <id> (optional; used only for runner bookkeeping)
  • --inputs <a;b;c> (optional; defaults to the four Inputs listed above)
  • --outputs <timeline_rel;figures_rel> (optional; defaults to outline/timeline.md;outline/figures.md)
  • --checkpoint <C#> (optional; ignored by the helper)

Examples

  • Generate timeline + figures with defaults: python.codex/skills/survey-visuals/scripts/run.py --workspace workspaces/<ws>
  • Generate to custom output paths: python.codex/skills/survey-visuals/scripts/run.py --workspace workspaces/<ws> --outputs outline/timeline.md;outline/figures.md

Notes

  • The helper is intentionally minimal and never overwrites non-placeholder artifacts.
  • In strict mode it blocks only if placeholder markers remain (and if minimum timeline/figure requirements are not met).

Troubleshooting

Issue: timeline is thin or citation-free

Fix:

  • Prefer fewer, higher-signal milestones, but ensure each bullet has >=1 [@...].
  • Route upstream if notes are thin: strengthen paper-notes / evidence-draft rather than padding.

Issue: figure specs read like prose

Fix:

  • Keep specs as draw-instructions: purpose + elements + what each element is supported by (cite keys).
  • Move narrative explanation into the main text; this file should stay non-prose.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

27.73%
按下载量换算62

Gemini CLI

23.4%
按下载量换算53

Cursor

17.42%
按下载量换算39

Codex

12.34%
按下载量换算28

OpenCode

7.54%
按下载量换算17

Antigravity

2.94%
按下载量换算7

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。

来源信息

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