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Skills/design-creative/Abstract Fig

Abstract Fig

REVIEW · 66
Community indexed

Codex skill for editable draw.io graphical abstracts and manuscript concept figures

Downloads0
Stars16
Version1.0.0
Quality70/100 · Strong
Trust66/100 · Sandbox only
Audit80/100 · Needs review

Supply asset profile

Research and knowledge work

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Browse track

Scenario

RAG and knowledge

I need my agent to build a RAG workflow over documents and retrieve reliable context.

Agent fit

Claude Code + OpenAI Agents + CLI

Codex, Claude Code, Cursor, CLI, or custom agents.

Install

Ready

npx skills add keros68/abstract-fig

Maintenance

fresh

2d since push

Risk

Needs review

Low GitHub adoption signal

GitHub quality

16

70/100 quality · 74/100 trust

Coverage tags

ResearchRAG and knowledgedesign-creativedrawiographical-abstract

Review notes

Low GitHub adoption signal · Quality score needs review

Agent adoption scorecard

Trust, audit, and install readiness at a glance

These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.

Quality

Strong
70

Solid option that is likely worth shortlisting for production workflows.

Trust

Sandbox only
66

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

Audit

Needs review
80

Install readiness, security metadata, maintenance, and adoption risk.

Trust Score v5

Human review before install

Run only in a sandbox and compare close alternatives before using it for real work.

PythonCodexClaude CodeCursorOpenAgentSkill CLI

Stars

16 GitHub stars

Repo activity

16 stars, 1 forks

Maintenance

2d since push

License

MIT

Install

npx skills add keros68/abstract-fig

Install safety

standard package or runtime install path

Permission surface

shell or command execution, filesystem or document access

Agent outcomes

No agent outcome data yet

Docs

Strong README/SKILL.md context

Risk summary

Review before production

  • Low GitHub adoption signal
  • Quality score needs review
  • GitHub adoption: 16 GitHub stars
  • Stars/forks activity: 16 stars, 1 forks; issue activity unavailable in current metadata

Install readiness

Install path available

  • Install path is available
  • Repository evidence is available
  • License is declared
  • No Agent Proven outcome evidence yet

Agent-readable metadata

Machine-readable decision data for this skill.

Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.

Open JSON

Suited tasks

  • Design and creative workflows
  • Claude Code teams
  • builders willing to evaluate younger projects
  • Inspect visual requirements

Suited agents

PythonCodexClaude CodeCursorOpenAgentSkill CLIOpenAI AgentsCLI

Install decision

Command
npx skills add keros68/abstract-fig
Policy
review
Human review
yes

Trust and risk

Trust
66/100
Audit
80/100
Risk level
Needs review

Outcome loop

Endpoint
/api/agent/outcome
Event ID
resolve
Outcomes
5

Install command

npx skills add keros68/abstract-fig
Public auditEval reportResolve APIInstall handoff

Do not use when

  • teams that need a vendor-supported SLA
  • production agents without a repository review
  • Low GitHub adoption signal
  • High-risk permission hints: Shell or command execution
  • Quality score needs review

Alternative

Frontend Design

163.5K stars

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Alternative

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163.5K stars

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Agent safety v2

52/100 · Avoid automatic install

Experimentalreview

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

Resolve via API

high

Shell or command execution

Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.

medium

Network access

Skill likely fetches remote pages, APIs, repositories, or external services.

medium

Filesystem access

Skill may read or write project files, documents, generated artifacts, or local workspace state.

  • High-risk permission hints: Shell or command execution
  • Low GitHub adoption signal

Install targets

Install this skill in your agent workflow

Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.

skill install

OpenAgentSkill CLI

Use the registry command when your workflow supports the OpenAgentSkill installer.

$ npx skills add keros68/abstract-fig

Agent resolve plan

Let an agent verify fit before installing.

The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.

Open text plan

Resolve JSON

/api/agent/resolve?task=Use%20Abstract%20Fig%20for%20an%20agent%20workflow&agent=codex&max_risk=medium

Resolve text

/api/agent/resolve?task=Use%20Abstract%20Fig%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text

Install handoff

/api/skills/keros68-abstract-fig/install

Agent should check

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Copy prompt

Task: Use Abstract Fig in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Abstract%20Fig%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/keros68-abstract-fig/install
Install command: npx skills add keros68/abstract-fig
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent handoff

Give an agent the install path, not another directory page.

Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.

Open install API

Install handoff

/api/skills/keros68-abstract-fig/install

LLM text format

/api/skills/keros68-abstract-fig/install?format=text

Find alternatives

/api/skills/search?q=Abstract%20Fig&limit=3

Agent prompt

Use Abstract Fig for this task. Review https://www.openagentskill.com/api/skills/keros68-abstract-fig/install, then install with: npx skills add keros68/abstract-fig

Registry metadata

Agent-readable profile for automatic skill selection.

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open manifest

Manifest

/api/registry/manifest/keros68-abstract-fig

LLM text

/api/registry/manifest/keros68-abstract-fig?format=text

Install alias

/api/registry/install/keros68-abstract-fig

Recommend

/api/registry/recommend?task=Use%20Abstract%20Fig%20in%20an%20agent%20workflow&limit=3

Agent fit

70/100

Design and creative

Use-case tags

Design and creativeCoding agentsRAG and knowledge

Platforms

Python, Claude Code, OpenAI Agents

Audit report

Needs review · 80/100

Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.

View audit reportView eval report

Agent decision cockpit

Fallback candidate for Design and creative

Prototype with this skill first; keep a fallback candidate ready.

70
Readiness
Prototype
Stage

Role in stack

Fallback candidate

Primary fit

Design and creative

Trust label

Prototype first

Install path

Command ready

Use when

  • Design and creative workflows
  • Claude Code teams
  • builders willing to evaluate younger projects

Evidence

  • recent repository activity
  • install command or GitHub repo available
  • 70/100 quality profile
  • 2 OpenAgentSkill engagement events

Review first

  • Low GitHub adoption signal

Implementation path

  1. 1Install it in a sandbox agent and run one Design and creative task end to end.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Trust profile

Sandbox only

Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.

66
Trust score

GitHub adoption

FIX

16 GitHub stars

Stars/forks activity

FIX

16 stars, 1 forks; issue activity unavailable in current metadata

Recent maintenance

PASS

2d since push

License clarity

PASS

MIT

Good signals

  • AI review approved
  • Install path is available
  • Repository evidence is available
  • Recently maintained repository
  • Install command has no obvious high-risk pattern
  • Outcome loop is ready but needs first real agent run

Review before install

  • Low GitHub adoption signal
  • Quality score needs review
  • GitHub adoption: 16 GitHub stars
  • Stars/forks activity: 16 stars, 1 forks; issue activity unavailable in current metadata
  • No real agent outcome reports yet
  • Human review required before unattended installation

Recommended action

Run only in a sandbox and compare close alternatives before using it for real work.

Quality profile

Strong candidate for agent workflows

Solid option that is likely worth shortlisting for production workflows.

70
GitHub stars
16
Freshness
2d ago
Install ready
Yes
License
MIT
Check before install: Low GitHub adoption signal

Workflow fit

Use this skill in these scenarios

Create assets

Design and creative

I need my agent to produce design assets, UI directions, presentations, or creative media workflows.

Build and ship code

Coding agents

I need a coding agent that can understand a repository, edit code, and review pull requests.

Search private knowledge

RAG and knowledge

I need my agent to build a RAG workflow over documents and retrieve reliable context.

Workflow fit

Add it to a complete workflow

Design, build, test, and ship interfaces

Frontend and UI

A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.

Inspect, patch, and verify code

Coding review agent

A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.

Ingest, retrieve, and cite

RAG knowledge base

A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.

Alternative shortlist

Compare before you install

Similar skills in this category, ranked with the same readiness and quality signals.

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Overview

# Abstract-Fig

生成可编辑论文图形摘要和概念模型图的 Codex skill:先用 Codex 里的 image2 制作论文主题元素,拆分为独立透明 PNG,嵌入 draw.io,文字框、箭头、边框、分组和标签全部保持可编辑。

目标不是一张不可编辑的 AI 大图,而是一个能在 draw.io 里继续拖拽、改字、换元素、调版面的 `.drawio` 文件。适合投稿论文的 graphical abstract、机制概念图、方法流程图和综合示意图。

> 中文为主,English version below.

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) [![Agent Skill](https://img.shields.io/badge/Agent%20Skill-SKILL.md-green.svg)](SKILL.md) [![draw.io](https://img.shields.io/badge/draw.io-editable%20.drawio-orange.svg)](https://app.diagrams.net/)

## 运行要求

只面向 Codex:完整流程依赖 Codex 里的 image2 生图能力。其他 agent 可以参考 `SKILL.md` 的流程思路,但没有 image2 或等价的生图与文件处理能力,就复现不了"生成元素 → 拆分元素 → 嵌入 draw.io"这条链。

## 使用场景

- 已有论文主线、审稿意见或修改建议,要转成正文概念图或 graphical abstract。 - 需要"图片元素 + 可编辑文字框 + 可编辑箭头"的投稿图,而不是整张贴图。 - 普通流程图太像模板,想加入含水介质、河流、农田、采样井、仪器、地貌等论文主题元素。 - 把已有草图或 draw.io 文件改成适合期刊正文的 boxed manuscript style。

## 功能

从论文内容提炼图件主线(如 `setting -> process/media -> evidence -> status/output`),判断图件类型,生图前先给出绘制方案供选择(agent 自主判断、风格菜单或自定义要求)。生成或复用 image2 元素表,把元素拆成多个透明 PNG,逐个作为独立图片对象嵌入 draw.io;科学逻辑用可编辑的文字框、分区框、箭头和标签表达。默认白底、细边框、少量配色、大字号,并检查压盖、箭头穿字、小字号、A4 缩放后不可读等常见排版问题。

交付物:一个 `.drawio` 文件 + `elements/` 透明 PNG 元素文件夹,外加嵌入检查结果和微调建议。默认不导出 PNG/PDF/SVG——先在 draw.io 里调到满意,再按期刊要求导出。

## 边界

- 不把整张 AI 生成图直接当成最终 draw.io 图。 - PNG 元素内部不能像矢量图一样逐笔编辑;可编辑的是元素位置、大小、替换关系,以及所有文字、边框、箭头和标签。 - 不凭空强化论文机制,不把概念假设画成已证实结论。 - 不替代作者对科学术语、图注、投稿格式和最终分辨率的人工复核。 - 元素质量取决于 image2 生成与拆分效果,复杂背景、阴影和细线可能要手动清理;投稿前建议导出 PDF 按 A4 或期刊栏宽再查一遍。

## 快速开始

在 Codex 里发送:

```text 请从 GitHub 安装这个 skill,并在之后需要制作论文 graphical abstract、概念模型图或可编辑 draw.io 投稿图时优先使用它: https://github.com/keros68/abstract-fig ```

装完重启或新开窗口:

```text 使用 $abstract-fig 根据这篇论文主线做一张可编辑 draw.io 图形摘要,要求先生成主题元素,再拆分嵌入到 draw.io。 ```

手动安装:

```bash git clone https://github.com/keros68/abstract-fig.git ~/.codex/skills/abstract-fig ```

做好的 `.drawio` 文件拖进 [draw.io 官方编辑器](https://app.diagrams.net/) 即可继续编辑;网页询问保存位置时选本地存储。

## 文件结构

- `SKILL.md` - skill 主说明和触发规则。 - `references/figure-types.md` - 图件类型选择规则。 - `referen

Platform Compatibility

pythonFULL

Technical Details

Version
1.0.0
License
MIT
Last Updated
7/23/2026
Published
7/23/2026

Frameworks & Tools

Python

Decision snapshot

Fallback candidate

70
Ready
Prototype
Stage

recent repository activity

Audit snapshot

Install review

Install and adoption review

80
Needs review
Security
83/100
Maintenance
100/100
Install
92/100
Open full auditOpen eval report

Agent-proven evidence

Agent Proven evidence

Outcome reports after resolve, review, install, and one narrow run.

0
Proven
Needs first agent runAuto-install: review firstLast: Unknown
Success rate
—
Recent failure
—
Outcomes
0
Output quality
—
Failed
0
Not relevant
0
Installs
0
Risk blocked
0
Setup needed
0
Production
0

No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.

Agent-Proven rankingOutcome contract

Install

Add to agent workflow

Free and open source. Review the audit before production use.

Compare AlternativesAuto-resolve PlanView on GitHubDocumentation

Growth loop

Share kit

X

Scenario-led draft for Abstract Fig, ready for a manual X post.

Curator note
The useful research skills are not search wrappers. They help agents keep sources attached.

Abstract Fig helps agents turn docs, data, or knowledge bases into grounded work.

16 stars

https://www.openagentskill.com/skills/keros68-abstract-fig?ref=x
#AIAgents
Open X draft
Optional reply with install command
Listing + install path for Abstract Fig:
https://www.openagentskill.com/skills/keros68-abstract-fig?ref=x

Install: npx skills add keros68/abstract-fig
Open reply draft

Listing source

Community indexed

Claimable

This listing was indexed from public sources and is not marked official until a maintainer claim is approved.

Creator
keros68
Source
keros68/abstract-fig
Indexed by
OpenAgentSkill community index

Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.

Claim this skill

Owner claim

Claim this skill listing

This community indexed listing is attributed to keros68 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.

Creator backlink kit

Add the evidence badges to your README

Show the canonical listing, current trust and audit signals, and real Agent Proven evidence where developers evaluate the repository.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/keros68-abstract-fig?metric=listed&label=Listed)](https://www.openagentskill.com/skills/keros68-abstract-fig)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/keros68-abstract-fig?metric=trust&label=Trust)](https://www.openagentskill.com/skills/keros68-abstract-fig)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/keros68-abstract-fig?metric=audit&label=Audit)](https://www.openagentskill.com/skills/keros68-abstract-fig/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/keros68-abstract-fig?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/keros68-abstract-fig)
Preview badge Open audit Creator Kit

Author

K

keros68

@keros68

Tags

drawiographical-abstractcodexskillresearch-figurespython

Platform Fit

Claude CodeOpenAI Agents

Health Signals

GitHub stars
16
Quality score
43/100
Last GitHub push
Jul 21, 2026
Framework hints
1
OpenAgentSkill views
2
Install copies
0
Outbound clicks
0

Community Signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & Safety

Sandbox only

66
  • GitHub adoption16 GitHub starsFIX
  • Stars/forks activity16 stars, 1 forks; issue activity unavailable in current metadataFIX
  • Recent maintenance2d since pushPASS
  • License clarityMITPASS
  • README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
  • Dependency/runtime riskcommand execution surfaceINFO

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OpenAgentSkill

The skill layer for AI agents: discover, compare, audit, and install reusable capabilities across Codex, Claude Code, Cursor, and agent runtimes.

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