What makes Paper Framework Figure Studio Pro notable?

1.4K downloads. Trust evidence available

How should Paper Framework Figure Studio Pro be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

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agentCLAWHUBUnverified

Paper Framework Figure Studio Pro

Use when the user wants to design, prompt, generate, critique, or integrate publication-ready research-paper framework figures: method overview diagrams, arc...

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.4k

Updated

Oct 10, 2026

Version

1.2.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.4K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.4K downloadsadoption · observed Oct 10, 2026
Latest release: 1.2.0release · observed May 5, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s177jw27anm32qt3dm1c7dq0jh851mjz:paper-framework-figure-studio-pro

Install using `clawhub skill install s177jw27anm32qt3dm1c7dq0jh851mjz:paper-framework-figure-studio-pro` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/c-narcissus/paper-framework-figure-studio-pro before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-c-narcissus-paper-framework-figure-studio-pro/snapshot"

Documentation

CLAWHUB

149,654 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: paper-framework-figure-studio-pro
license: MIT-0
description: "Use when the user wants to design, prompt, generate, critique, or integrate publication-ready research-paper framework figures: method overview diagrams, architecture diagrams, pipeline/process diagrams, agent workflows, system/data-flow figures, mechanism-intuition figures, case walkthrough panels, and reviewer-facing schematic figures. Generated from research-paper-figure-skill-factory v1.0.1 with full-feasible local PDF evidence, startup-plan-only first replies, strict text/image separation, mandatory text-candidate to visual-candidate setup to image-only candidate board to candidate-review selection workflow, optional sample images, ChatGPT web Create image / ChatGPT Images 2.0, Codex $imagegen first, all-step/current-position state footers, and next-question help in every text reply."
metadata:
  display_name: Paper Framework Figure Studio Pro
  version: "1.2.0"
  author: OpenAI
  tags:
    - research-figure
    - paper-framework
    - method-framework
    - architecture-diagram
    - pipeline-diagram
    - agent-workflow
    - candidate-image-bridge
    - imagegen
    - chatgpt-images-2
    - clawhub
    - openclaw
  compatibility: Codex, ChatGPT web, OpenClaw, ClawHub marketplace. Requires image-generation capability for rendering.
  openclaw:
    skillKey: paper-framework-figure-studio-pro
---

# Paper Framework Figure Studio Pro

This skill designs publication-ready raster framework figures for computer-science research papers. Use it for method overviews, architecture diagrams, pipelines, agent workflows, system/data-flow figures, mechanism-intuition figures, case walkthroughs, and reviewer-facing schematic figures.

It was regenerated with `research-paper-figure-skill-factory` v1.0.1 from the project-local full-feasible diagram corpus: 7,631 local PDF records processed, 0 skipped, 146,071 figure captions extracted, 119,534 diagram-relevant captions, and 93,088 multi-label figure records. Framework-relevant evidence includes method-framework, architecture, pipeline/process, agent-workflow, mechanism, and case-walkthrough patterns. Representative rendered pages are audit aids only, not the corpus size.

## Non-Negotiable Contract

### First Trigger

On the first reply in a new project, output only a startup plan. Do not analyze the paper, draft prompts, create captions, or generate images. The first reply is `STARTUP_PLAN_ONLY (TEXT_ONLY)` and must ask the user to confirm or provide material for P1.

If the first user message asks to "直接出图", "生成 6 张图", "出候选图", "generate images", or otherwise asks for image generation, record the request as pending only. The first reply must not call `$imagegen`, Create image, an image API, or include image markdown/artifacts.

### Mandatory Candidate-Image Bridge

After any multi-option text decision, do not move directly to final prompt, final image generation, caption, or text-only locking. Use this mandatory bridge:

1. `TEXT_ONL

README.md

# Paper Framework Figure Studio Pro

## 中文

`paper-framework-figure-studio-pro` 用于帮助研究者为论文生成 framework diagram、method diagram、pipeline diagram、architecture diagram 和 agent workflow 等框架图。它适合把论文 PDF、摘要、方法说明或草稿转化为可比较的制图方案、候选图、修改建议、caption 和图注说明。

### 推荐使用方式

优先在 ChatGPT 网页版中使用，并选择 **Extended thinking**。网页版更适合完成完整的论文理解、候选图生成和多轮修图流程。

如果接下来的步骤是生成图片，最好在 ChatGPT 网页版中手动选择 **Create image** 模式，再让它继续生成候选图或最终图。

在 Codex 里也可以尝试使用，但可能会遇到图像生成或上下文处理问题，而且会比较费 token。除非你明确需要在本地工程目录中整理文件、改 skill 或生成配套文档，否则不建议把主要制图流程放在 Codex 里完成。

### ChatGPT 网页版使用步骤

1. 把 `paper-framework-figure-studio-pro-v1.2.0-skill.zip` 放进 ChatGPT 的 Sources。
2. 把论文 PDF 也放进 Sources，例如 `semiDFL.pdf`。
3. 选择 Extended thinking。
4. 输入类似下面的 prompt：

```text
请严格按照 paper-framework-figure-studio-pro-v1.2.0-skill.zip 里 skill 的步骤，对 semiDFL.pdf 绘制 diagram。不要参考 semiDFL.pdf 里面已有的 diagram。
```

如果你的论文文件名不是 `semiDFL.pdf`，请把 prompt 里的文件名替换为实际上传到 Sources 的文件名。

当 skill 已经完成文字方案比较，并提示下一步要生成候选图或最终图时，建议手动切换到 **Create image** 模式后再继续。

### 制图流程

1. 提供论文 PDF、摘要、方法说明、目标章节或已有草稿。
2. 说明是否要避开论文中已有 diagram，以及是否提供参考图。
3. Skill 先判断这张图更适合 framework、architecture、pipeline、workflow 还是 mechanism diagram。
4. 先生成 4-6 个文字方案，通常是 6 个。
5. 选择或确认候选图方向；如果有参考图，可以说明每张图只参考布局、风格、信息密度、标签或配色中的哪些属性。
6. 生成多张候选图或示意图供比较。
7. 从候选图中选择最接近的一张，或指出需要修改的地方。
8. 根据选择继续生成正式版本或修订版本。
9. 最后整理 caption、legend 和正文中的图说明文字。

## English

`paper-framework-figure-studio-pro` helps researchers create framework diagrams, method diagrams, pipeline diagrams, architecture diagrams, and agent workflows for research papers. It turns a paper PDF, abstract, method description, or draft notes into comparable diagram directions, candidate figures, revision guidance, captions, and figure descriptions.

### Recommended Use

Prefer using this skill in the ChatGPT web app with **Extended thinking** enabled. The web app is better suited for the full workflow: paper understanding, candidate figure generation, and iterative figure revision.

If the next step is image generation, it is best to manually select **Create image** mode in the ChatGPT web app before asking it to generate candidate figures or the final figure.

You can also try it in Codex, but image generation and context handling may be less reliable, and it can consume many tokens. Unless you specifically need local file organization, skill editing, or repository documentation, the main figure-making workflow is better done in ChatGPT web.

### ChatGPT Web Usage

1. Add `paper-framework-figure-studio-pro-v1.2.0-skill.zip` to ChatGPT Sources.
2. Add the paper PDF to Sources as well, for example `semiDFL.pdf`.
3. Select Extended thinking.
4. Type a prompt like this:

```text
Please strictly follow the workflow in paper-framework-figure-studio-pro-v1.2.0-skill.zip to draw a diagram for semiDFL.pdf. Do not refer to any existing diagram inside semiDFL.pdf.
```

If your paper file is not named `semiDFL.pdf`, replace the file name in the prompt with the exact file name uploaded to Sources.

When the skill has finished comparing text di

_meta.json

{
  "ownerId": "kn7fxns1xpr6z67w885my7d7k98506vv",
  "slug": "paper-framework-figure-studio-pro",
  "version": "1.2.0",
  "publishedAt": 1777985884848
}

references/builder-time-acquisition-report.md

# Builder-Time Acquisition Report

Generated by `research-paper-figure-skill-factory` v1.0.1 for `paper-framework-figure-studio-pro` v1.2.0.

## Source

The skill uses the previously extracted project-local full-feasible diagram corpus, rooted at `research-paper-diagram-generation-corpus/`, as builder-time evidence. No new web download was needed for this generation because the local PDF index and extraction artifacts already existed.

## Processing Scope

- Scope: `all_accessible_relevant_pdfs`.
- Candidate PDFs: 7,631.
- Accessible PDFs: 7,631.
- Processed PDFs: 7,631.
- Skipped PDFs: 0.
- Skipped reasons: none recorded.
- Representative rendered pages: 96 audit aids, not the corpus size.

## Framework Evidence Focus

The generated skill narrows the broader diagram taxonomy to framework-related figure production: method frameworks, architecture diagrams, pipeline/process diagrams, agent workflows, system/data-flow diagrams, mechanism-intuition figures, and case walkthroughs.

Production-grade lock is supported because the skill includes source-corpus notes, an evidence-map index, an evidence-lineage summary, and framework-specific taxonomy/pattern references.

references/evidence-lineage-summary.md

# Evidence Lineage Summary

The full local evidence map supports these skill claims:

1. Framework-diagram routing must distinguish method framework, architecture, pipeline/process, agent workflow, system/data flow, graph/network, mechanism, walkthrough, evidence-board, taxonomy, data/protocol, failure, and theory/proof-intuition layouts.
2. Reader questions differ across diagrams: system identity, process sequence, entity relation, mechanism, case behavior, contribution boundary, and claim support.
3. Density must be selected before rendering because framework figures range from clean overview panels to dense evidence-linked boards.
4. Panel choreography is a first-class design decision for multi-panel research figures.
5. Evidence diagrams must not invent results; they require user-provided metrics, comparisons, or qualitative examples.
6. Routing must be multi-label: one PDF or one diagram can support multiple labels before a primary production subtype is selected.
7. When multiple schemes are plausible, the skill should move toward generated candidate images or schematic candidates, usually 6, instead of asking the user to compare only text.

These claims are backed by `research-paper-diagram-generation-corpus/extracted/evidence_map.json`.

## Full-Corpus Counts

- Processed local PDF records: 7,631.
- Verified official oral PDFs: 3,356.
- Supplemental local PDFs: 4,275.
- Extracted figure captions: 146,071.
- Diagram-relevant captions: 119,534.
- Multi-label diagram records: 93,088.
- Representative rendered pages: 96.

## Framework-Relevant Label Coverage

The label counts are multi-label and can sum above the number of diagram-relevant captions.

| Label | Caption count | Paper count | Representative pages |
|---|---:|---:|---:|
| method_framework | 16,565 | 5,267 | 8 |
| architecture | 14,651 | 4,256 | 8 |
| pipeline_process | 28,981 | 5,878 | 8 |
| agent_workflow | 16,271 | 2,228 | 8 |
| graph_network | 26,059 | 4,335 | 8 |
| mechanism_intuition | 42,578 | 5,947 | 8 |
| case_walkthrough | 35,822 | 6,465 | 8 |
| evidence_board | 63,404 | 6,947 | 8 |
| data_benchmark_protocol | 25,583 | 4,881 | 8 |
| failure_limitation | 20,719 | 4,570 | 8 |
| taxonomy_design_space | 5,993 | 2,141 | 8 |
| theory_proof_intuition | 9,985 | 3,286 | 8 |
| general_diagram_or_figure | 17,072 | 3,160 | 0 |

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