Paper Framework Figure Studio Pro

- Added license information to SKILL.md (MIT-0). - Added OpenClaw-specific metadata under `openclaw` in SKILL.md. - Moved compatibility information into metadata. - Added missing agents/openai.yaml file.

No functional or content changes in this version. - Version bumped from 1.4.2 to 1.4.3 in skill metadata. - No other modifications detected.

**Paper Framework Figure Studio Pro v1.4.2** Major update: Improved workflow structure, explicit state management, and detailed setup/usage guidance for multi-round figure design. - Added robust documentation files (templates, examples, references, publishing guides) to support consistent multi-round, stateful workflow. - Enforced strict turn-separation protocol: all planning and approval steps are text-only; image rendering occurs only after explicit user confirmation. - Introduced first-contact and first-turn protocols to recommend but not require upstream deep-reading reports, guiding users on preferred input and next steps. - Clarified non-negotiable rules around human approval, state tracking, and workflow for image candidate generation and selection. - Updated compatibility metadata and improved clarity on workflow expectations, next step guidance, and decision points. - Removed legacy and redundant documentation to streamline onboarding and publishing.

Paper Framework Figure Studio Pro is a multi-round scientific diagram co-designer specialized for paper framework diagrams and method overview figures in top-tier computer science papers. It helps transform a paper deep-reading report, method description, or model overview into publication-ready figures through an iterative human-in-the-loop workflow. Instead of producing a single figure in one shot, the skill guides the user through structured rounds of framework-figure design: first selecting a high-level figure family, then narrowing down substyles, layout, information density, and local visual elements. After each round, it generates multiple candidate diagrams, lets the user choose or combine directions, records preferences, and updates the design state before continuing. The skill is optimized for reviewer communication efficiency. It prioritizes clear problem framing, framework structure, module interactions, key novelty, and why-the-method-works comparisons. It supports several figure families commonly seen in recent top-tier CS papers, including classic framework overview, modern modular card layouts, mechanism-explanation figures with intermediate snapshots, and design-forward scientific illustration styles. After generating the final figure, the skill explicitly asks whether the user also wants supporting figure text, such as short in-figure labels, a polished figure caption, panel-by-panel explanation text, or slide-friendly annotation text.