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Research Paper Figure Skill Factory

作者 c-narcissus · GitHub ↗ · v1.0.1 · MIT-0
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在 OpenClaw 中安装
/install research-paper-figure-skill-factory
功能描述
Use when the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful lite...
使用说明 (SKILL.md)

Research Paper Figure Skill Factory

This skill is a two-layer research-paper figure Skill Factory.

  1. Skill Builder layer: build or patch a reusable specialized figure-making skill for one paper-figure class by acquiring lawful source material, extracting figure evidence, building a taxonomy, generating the skill package, testing it, and locking it.
  2. Figure Production layer: after a specialized skill is locked, use that generated skill to design, compare, render, review, and integrate concrete figures for arbitrary target papers of the same figure class.

Non-Negotiable Contract

First Trigger

On first trigger, output only a startup plan. Do not analyze a paper, build a taxonomy, create candidate schemes, draft prompts, or generate images. The first reply is STARTUP_PLAN_ONLY (TEXT_ONLY).

If the first user message asks for images, record the request as pending only. The first reply must not call Create image, $imagegen, an image API, or include image artifacts.

Specialized-Skill-First Builder Rule

The normal route is:

figure-class goal -> corpus plan -> lawful acquisition/local corpus -> evidence extraction -> taxonomy -> specialized skill blueprint -> generated specialized skill -> tests/patches -> locked skill -> target-paper production.

Do not jump from source papers directly to one concrete figure unless the user explicitly chooses a full production fast-track. If fast-tracking, record the skipped builder steps and fallback skill/taxonomy.

Full-Feasible Corpus Rule

When local PDFs, a paper index, or retrieval manifests exist, enumerate the full relevant candidate set and process as many accessible relevant PDFs as feasible. A small sample can support only a limited/pilot/fallback lock unless the user explicitly accepts that limitation. Representative rendered pages are audit aids only, not the corpus size.

Mandatory Candidate-Image Bridge

Every generated specialized figure-making skill must include a hard workflow bridge after any multi-option text decision:

  1. TEXT_ONLY candidate text turn: present 4-6 text candidates, normally 6.
  2. TEXT_ONLY visual candidate setup turn: define candidate count, varied axis, fixed elements, rendering route, and what the user should compare.
  3. IMAGE_ONLY candidate-board turn: generate/display 4-6 candidate images or schematic candidates, normally 6.
  4. TEXT_ONLY candidate-review turn: record the previous image batch, compare candidates, recommend one direction, and ask the user to select, revise, or request another board.

This bridge is mandatory after candidate schemes, subtype choices, layout choices, style choices, metaphor choices, density choices, and prompt alternatives. The generated skill must not move directly from 4-6 text candidates to final prompt construction, final image generation, caption writing, or text-only locking unless the user explicitly says to skip image candidates and stay text-only. If skipped, record visual_candidate_board_skipped_by_user: true.

Generated skill lock/test must fail if:

  • the workflow lacks a dedicated visual candidate setup step;
  • the workflow lacks a dedicated IMAGE_ONLY candidate-board step before direction lock;
  • examples show text candidates followed directly by final prompt or final image generation;
  • the state footer cannot record visual_candidate_board_status, candidate_image_batch_id, and selected_visual_candidate;
  • multi-option next prompts do not ask the user to generate/display multiple candidate images or schematic candidates, normally 6.

Strict Text/Image Separation

Every response is exactly one modality:

  • TEXT_ONLY: planning, intake, diagnosis, candidate text, candidate-board setup, prompt writing, critique, status, and next prompts.
  • IMAGE_ONLY: image generation only. No prose, captions, critique, prompt text, or state footer.

If a reply emits any visible text, it must not generate images in the same response. If the user confirms generation and state is sufficient, the next assistant response may be IMAGE_ONLY only.

Rendering Route

For candidate boards, draft candidates, final diagrams, and revisions:

  1. ChatGPT web must use Create image through ChatGPT Images 2.0.
  2. Codex must use the $imagegen skill first.
  3. If $imagegen is unavailable in Codex, use ChatGPT Images 2.0 API or another approved image-generation API.
  4. Native bitmap outputs such as PNG, JPG, JPEG, and WebP are allowed when produced by the approved image route.
  5. Do not use SVG, Mermaid, TikZ, Graphviz, HTML/CSS, canvas, matplotlib, filesystem code drawing, or code-rendered/exported figures as candidate images, draft images, final visuals, or fallbacks.

Reference Images

Generated specialized skills must support optional sample/reference images. If the user provides multiple images, ask which attributes to borrow from each image: style, layout, panel rhythm, density, content-detail level, labels, color semantics, callout grammar, or negative-reference constraints.

Every Text Reply

Every TEXT_ONLY reply from this factory and from generated specialized skills must include:

  • 当前执行计划
  • substantive work for the current step
  • 默认推荐
  • 当前状态与产物
  • 下一步你可以这样问

The state footer must list all steps plus the current position and the response mode of every step. The first copyable next prompt must use:

请使用**\x3C当前skill名称>**,执行,根据当前状态,下一步执行:...

Always include:

请使用**\x3C当前skill名称>**,根据当前状态,提供下一步提问建议。

Skill Builder Workflow

Step Layer Mode Purpose Output
S0 Startup STARTUP_PLAN_ONLY (TEXT_ONLY) Show the complete two-layer plan only Startup plan
B1 Skill Builder TEXT_ONLY Define target figure class and generated skill goal Figure-class brief
B2 Skill Builder TEXT_ONLY Define corpus scope, venues, keywords, and lawful acquisition route Corpus plan
B3 Skill Builder TEXT_ONLY Acquire or organize open/user-authorized PDFs and manifests Local corpus + retrieval manifest
B4 Skill Builder TEXT_ONLY Extract paper cards, captions, figure inventory, labels, and visual observations Evidence artifacts
B5 Skill Builder TEXT_ONLY Build evidence-backed figure-class taxonomy Taxonomy + lineage
B6 Skill Builder TEXT_ONLY Convert taxonomy into specialized skill blueprint Blueprint
B7 Skill Builder TEXT_ONLY Generate specialized skill package Skill folder/package
B8 Skill Builder TEXT_ONLY Test and patch startup, state, candidate-board, rendering, and prompt behavior Test report + patches
B9 Skill Builder TEXT_ONLY Lock generated skill for reusable production Locked skill with version/scope

Required Generated Figure-Production Workflow

Every generated specialized figure-making skill must use this expanded production workflow, or a stricter equivalent with the same mandatory candidate-image bridge:

Step Mode Purpose Output
P1 TEXT_ONLY Intake target-paper material, target slot, constraints, and optional sample images Material status
P2 TEXT_ONLY Diagnose figure need and multi-label subtype routing Subtype candidates + default route
P3 TEXT_ONLY Define reader effect and produce 4-6 text candidate schemes, normally 6 Text candidates + required visual-candidate next action
P4 TEXT_ONLY Set up visual candidate board: candidate count, varied axis, fixed content, route, comparison criteria Candidate-board brief
P5 IMAGE_ONLY Generate/display 4-6 candidate images or schematic candidates, normally 6 Image candidates only
P6 TEXT_ONLY Record the image batch, compare candidates, recommend one, and lock or revise direction Selected/revised visual direction
P7 TEXT_ONLY Build final content architecture and formal image brief/prompt for the selected direction Final image brief
P8 IMAGE_ONLY Generate formal figure candidate or revision batch through the approved image route Formal image candidates only
P9 TEXT_ONLY Review, refine, caption, legend, body insertion, and handoff text Final paper text package

Rules for this workflow:

  • P3 must not ask the user to choose only from text as the primary route. Its first recommended next prompt must be to generate/display 6 candidate images or schematic candidates.
  • P4 is required before P5 unless the immediately preceding user message already confirms the board count, varied axis, fixed elements, and rendering route.
  • P5 is not a final figure stage. It is a visual selection stage.
  • P6 must happen after P5 and must record the image batch before any final prompt or caption work.
  • P7/P8 may only occur after a direction is selected or the user explicitly requests a formal generation despite unresolved candidates.
  • Any generated skill may add more domain-specific steps, but it must not remove P4/P5/P6 or collapse them into a mixed text+image response.

Generated Skill Package Requirements

Generated specialized skills must include the candidate-image bridge in:

  • SKILL.md
  • metadata.json
  • agents/openai.yaml
  • references/workflow-and-state-contract.md
  • references/visual-style-and-board-protocol.md
  • references/prompt-generation-policy.md
  • templates/state-footer-template.md
  • templates/figure-brief-template.md
  • templates/prompt-template.md
  • examples, especially startup, text-candidate, visual-board setup, image-only board, and candidate-review examples
  • release checklist and starter prompts

The release checklist must include a failing test for the exact bug this patch fixes: “after 4-6 text candidates or layout/style-axis setup, the generated skill still has no separate candidate-image generation step.”

Reference Loading Order

Load references as needed:

  1. references/master-workflow.md
  2. references/generated-specialized-skill-output-spec.md
  3. references/generated-skill-multi-candidate-policy.md
  4. references/visual-first-decision-board-protocol.md
  5. references/startup-plan-step-output-map.md
  6. references/planning-state-and-navigation-contract.md
  7. references/prompt-generation-and-rendering-policy.md
  8. references/strict-text-image-turn-separation-policy.md
  9. templates/specialized_skill_blueprint_template.md
  10. templates/state_footer_template.md

Version Note

Version 1.0.1 makes the candidate-image bridge mandatory in generated figure-making skills. A generated skill must no longer stop at text candidates, layout/style axis decisions, or visual-board suggestions; it must provide explicit steps for candidate-board setup, image-only generation of multiple candidates, and text-only candidate review/selection.

安全使用建议
This skill appears safe to install as an instruction-only workflow, but use it with a scoped research corpus, verify any generated skill ZIP before installing it elsewhere, and confirm image-generation steps before sending confidential paper content to external image tools.
功能分析
Type: OpenClaw Skill Name: research-paper-figure-skill-factory Version: 1.0.1 The bundle is a highly structured 'Skill Factory' designed to create specialized AI agents for generating research paper figures. It implements a complex two-layer workflow (Skill Builder and Figure Production) that enforces strict state management, text/image separation, and a multi-candidate selection process. While the skill requires significant capabilities—including web search for literature discovery, PDF processing for evidence extraction, and file system access to package generated skills—the instructions (SKILL.md and references) are consistently aligned with its stated scientific purpose. There is no evidence of malicious intent, data exfiltration, or unauthorized execution; the 'prompt injection' surface is used legitimately to constrain the agent's behavior for reliability and output quality.
能力标签
crypto
能力评估
Purpose & Capability
The stated purpose, templates, and references consistently describe a research-paper figure skill factory. The notable capabilities—local corpus processing, generated specialized skills, and image generation—are disclosed and aligned with that purpose.
Instruction Scope
The skill imposes a strict workflow with text-only planning, multi-candidate image boards, and image-only generation turns. This is purpose-aligned, but users should expect the workflow to prefer 4-6, usually 6, candidate images before locking a visual direction.
Install Mechanism
There is no install script or code execution in the provided artifacts. However, the skill is designed to generate and package new reusable skills, so generated ZIPs should be reviewed before installation.
Credentials
The skill expects lawful or user-authorized literature/PDF inputs and creates local corpus/extraction artifacts. This is proportionate for research-figure work, but users should keep the corpus scoped to materials they intend to share with the agent.
Persistence & Privilege
No credentials, background services, or privileged install steps are declared. The skill does preserve workflow state and extracted corpus artifacts, which can carry forward research content across steps or sessions.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install research-paper-figure-skill-factory
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /research-paper-figure-skill-factory 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
- Improved and clarified documentation in SKILL.md, elaborating required workflows, rules, and step-by-step guidance. - Detailed "Non-Negotiable Contract" outlining startup plan restrictions, candidate-image workflow, strict text/image separation, and rendering routes. - Defined complete two-layer Skill Factory workflow, with explicit step-by-step process requirements and TABLE. - Added mandatory conventions for every response, state tracking, and user prompt recommendations. - Specified compatibility, tags, and usage metadata for integrations and discoverability. - No functional code or logic changes described; this version focuses on specification and operational guarantees.
元数据
Slug research-paper-figure-skill-factory
版本 1.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Research Paper Figure Skill Factory 是什么?

Use when the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful lite... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 39 次。

如何安装 Research Paper Figure Skill Factory?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install research-paper-figure-skill-factory」即可一键安装,无需额外配置。

Research Paper Figure Skill Factory 是免费的吗?

是的,Research Paper Figure Skill Factory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Research Paper Figure Skill Factory 支持哪些平台?

Research Paper Figure Skill Factory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Research Paper Figure Skill Factory?

由 c-narcissus(@c-narcissus)开发并维护,当前版本 v1.0.1。

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