Nature-Style Scientific Figures
Yuan1z0825/nature-skills
Creates, revises, audits and exports manuscript-ready scientific figures in Python or R, and routes AI-generated graphical abstracts to a separate workflow.
Routes a full mathematical-modeling contest paper from the raw problem files through modeling, reproducible code, evidence checks and a final Word document with native equations.
Install MathModel Paper Workflow Orchestrator
$ npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-workflow-orchestrator --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/yushui2022/MathModel-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/trae/.trae/skills/paper-workflow-orchestrator .claude/skills/paper-workflow-orchestrator && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "paper-workflow-orchestrator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-workflow-orchestrator into .claude/skills/paper-workflow-orchestrator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-workflow-orchestrator", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-workflow-orchestratorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-workflow-orchestrator --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yushui2022/MathModel-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/trae/.trae/skills/paper-workflow-orchestrator .agents/skills/paper-workflow-orchestrator && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "paper-workflow-orchestrator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-workflow-orchestrator into .agents/skills/paper-workflow-orchestrator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-workflow-orchestrator", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-workflow-orchestrator --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yushui2022/MathModel-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/trae/.trae/skills/paper-workflow-orchestrator .cursor/skills/paper-workflow-orchestrator && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "paper-workflow-orchestrator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-workflow-orchestrator into .cursor/skills/paper-workflow-orchestrator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-workflow-orchestrator", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/yushui2022/MathModel-Skill.git --path packages/trae/.trae/skills/paper-workflow-orchestrator--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-workflow-orchestrator --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yushui2022/MathModel-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/trae/.trae/skills/paper-workflow-orchestrator .gemini/skills/paper-workflow-orchestrator && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "paper-workflow-orchestrator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-workflow-orchestrator into .gemini/skills/paper-workflow-orchestrator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-workflow-orchestrator", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install yushui2022/MathModel-Skill paper-workflow-orchestratorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/yushui2022/MathModel-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/trae/.trae/skills/paper-workflow-orchestrator .github/skills/paper-workflow-orchestrator && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "paper-workflow-orchestrator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-workflow-orchestrator into .github/skills/paper-workflow-orchestrator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-workflow-orchestrator", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-workflow-orchestrator --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yushui2022/MathModel-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/trae/.trae/skills/paper-workflow-orchestrator .opencode/skills/paper-workflow-orchestrator && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "paper-workflow-orchestrator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-workflow-orchestrator into .opencode/skills/paper-workflow-orchestrator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-workflow-orchestrator", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
paper-workflow-orchestrator- GitHub stars
- 454
- Token cost
- ~1.6k tokens
- SKILL.md length
- 550 words
- Files
- 7 (incl. scripts)
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- MIT
At a glance
Routes a full mathematical-modeling contest paper from the raw problem files through modeling, reproducible code, evidence checks and a final Word document with native equations.
- Starting a complete mathematical-modeling contest paper from problem files
- SKILL.md covers Start Or Resume, S0-S8, Formal Outputs and Non-Negotiable Invariants, plus 1 more section
- Runs Python scripts from its folder; calls python
- Resuming a contest paper workflow after a previous session stopped partway
What it does
This skill is the single entry point for a complete contest-paper request in a mathematical modeling workflow aimed at strong models that can hold a long evidence chain, as opposed to a separate Pro mode that runs multi-agent tournaments with approval checkpoints. Work starts or resumes by running a preflight check and a workflow guard status script from the contest project root, then reading a workflow_guard_report.json file for the recommended next skill and action, treating the current files and hashes as authoritative over conversational memory.
The process moves through numbered stages: S0 inventories input files, hashes them and rejects mixed contest editions; S1 produces a traceable problem analysis naming every question, constraint and required output; S2 routes to a model and rubric selection step and optionally harvests external data with source identity kept; S3 produces a data-cleaning and visualization plan from only the files the input manifest classifies; and S4 writes question-specific, reproducible modeling code that emits machine-readable result contracts. Later stages, referenced but not fully shown, continue toward real execution.
Downstream skills are not run until their guard requirement passes, and after each child skill finishes, control returns to this orchestrator to re-evaluate status before continuing.
When your agent uses it
- Starting a complete mathematical-modeling contest paper from problem files
- Resuming a contest paper workflow after a previous session stopped partway
- Checking which stage of the paper pipeline is next and what it still needs
- Keeping a long paper-writing workflow consistent across many steps
Example prompts
- “Start the Standard orchestrator on the problem files in this contest folder.”
- “Resume my MathModel paper workflow and tell me what stage comes next.”
- “Check whether my input files are a mixed edition before we go further.”
- “Run the data cleaning and visualization plan step for this contest problem.”
Requirements
- Python to run the bundled preflight, workflow guard and orchestration scripts
- A contest project folder laid out with a problem_files directory
What it can do on your machine
Read from SKILL.md and the folder at commit 7712876. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 5 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
MathModel Paper Workflow Orchestrator loads about 1.6k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 550 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from yushui2022/MathModel-Skill at commit 7712876, republished under its MIT licence (© yushui2022). 550 words, ~1,597 tokens.
Download SKILL.mdSave it as
.claude/skills/paper-workflow-orchestrator/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- paper-workflow-orchestrator
- description
- Run or resume the complete Standard mathematical-modeling workflow from contest files through reproducible evidence, adaptive formal writing, native-equation Word output, and final render QA. Use as the entry point for complete-paper requests.
MathModel Standard Orchestrator
Use this skill as the only entry router for a complete competition-paper task. Standard targets strong models that can maintain a long evidence chain and execute tools reliably while keeping cost controlled. It does not use Pro multi-agent tournaments or approval checkpoints.
Start Or Resume
From the contest project root, run:
python .trae/skills/paper-workflow-orchestrator/scripts/preflight_check.py
python .trae/skills/paper-workflow-orchestrator/scripts/workflow_guard.py --statusRead paper_output/qa/workflow_guard_report.json and follow recommended_skill plus next_action. The current files and hashes override conversational memory.
Do not run downstream skills before their guard requirement passes. After a child skill finishes, return here and evaluate status again.
S0-S8
S0 Input Admission
preflight_check.py inventories problem_files/, hashes every input, checks runtime dependencies, prepares paper_output/, and rejects mixed MathModel editions. Required outputs:
paper_output/preflight_report.jsonpaper_output/input_manifest.jsonpaper_output/OUTPUT_LAYOUT.md
S1 Problem Analysis
Use $problem-doc-model-selector to create paper_output/step1/problem_analysis.json. Every question, attachment, field, objective, constraint, ambiguity, and required output must be traceable.
S2 Model And Rubric Route
Use $modeling-paper-rubric-and-model-selector. Produce:
paper_output/plan/model_route.jsonpaper_output/plan/rubric_alignment.jsonpaper_output/plan/scoring_strategy.md
Use $authoritative-data-harvester only when public external data is necessary. Keep source identity and retrieval notes.
S3 Data And Visualization Plan
Use $data-cleaning-and-visualization. Read only files classified in the input manifest and produce a fresh load report, data plan, visualization plan, figure index, and cleaned data. Contest-specific code belongs under paper_output/code/, never inside installed skills.
S4 Reproducible Model Code
Use $model-code-and-result-generator to write question-specific code under paper_output/code/modeling/, including run_modeling.py and per-question modules. Code must emit machine-readable result contracts.
S5 Real Execution
Run the modeling code. Preserve script, input, output, exit-code, size, and SHA-256 records in paper_output/results/run_manifest.json. Required evidence includes model results, finite metrics, conclusions, tables, and usable figures. Draft placeholders do not count.
S6 Evidence Gate
Use $quality-assurance-auditor and run official evidence validation:
python .trae/skills/quality-assurance-auditor/scripts/evidence_gate.py --mode officialDo not enter formal writing until paper_output/qa/evidence_gate_report.json is PASS and all recorded inputs are still fresh.
Show full SKILL.md (265 more words)Show less
S7 Adaptive Formal Writing
Use $paper-formal-writer as the sole formal author:
python .trae/skills/paper-formal-writer/scripts/build_paper_outline.py
python .trae/skills/paper-formal-writer/scripts/prepare_authoring.py --mode autoNormal competition papers use complete-section drafting, possibly over several turns. Preserve the formal writer's declared competition scope; a short report needs an explicit user-requested scope and reason. Audit every draft with validate_authoring.py --section; global repeated failure falls back to section mode. A section’s second repeated category creates a micro-repair route; only then may $paper-micro-unit-generator repair the queued location. The third repeated category blocks S7 and suggests Lite without switching automatically.
After every active unit passes:
python .trae/skills/paper-formal-writer/scripts/assemble_sections.py
python .trae/skills/paper-formal-writer/scripts/validate_authoring.py --assembledThe Agent must then globally revise the full assembly into paper_output/final_paper_source.md; a copy-only promotion is rejected. Finish with:
python .trae/skills/paper-formal-writer/scripts/validate_authoring.py --final
python .trae/skills/paper-formal-writer/scripts/format_formal_docx.pyS8 Format And Render Gate
Run:
python .trae/skills/paper-formal-writer/scripts/check_paper_format.py --render requiredDelivery requires a fresh PASS in paper_output/format_check_report.json. Fix the reported source, formula, citation, figure/table, DOCX, pagination, or PDF issue and rerun; never edit the report to force PASS.
Formal Outputs
paper_output/plan/writing_plan.json
paper_output/context/authoring_state.json
paper_output/qa/draft_audit.json
paper_output/qa/repair_queue.json
paper_output/drafts/sections/*.md
paper_output/drafts/assembled_draft.md
paper_output/final_paper_source.md
paper_output/final_paper.docx
paper_output/format_check_report.jsonLegacy micro-unit and quickstart outputs remain under paper_output/drafts/legacy/ and paper_output/quickstart/. They can never satisfy S7.
Non-Negotiable Invariants
- Never invent model results, data sources, successful runs, citations, or validation.
- Every critical numeric claim must trace to current machine-readable evidence.
- Any upstream hash change invalidates dependent S6-S8 reports.
- Each included figure/table must exist, be indexed, cited, and interpreted.
- Formal formulas must become editable Word OMML; no screenshot or plain-text substitution.
- Do not expose skill names, guard commands, or workflow prose in the paper body.
- Do not write contest-specific code into installed skill directories.
- Install one MathModel edition per contest project.
Recovery
For an interrupted or long task:
python .trae/skills/paper-workflow-orchestrator/scripts/workflow_guard.py --status
python .trae/skills/context-memory-keeper/scripts/update_workflow_memory.pyRead the guard report, current stage contracts, and paper_output/context/workflow_memory.json; continue from the first failing stage instead of replaying completed work.
© yushui2022, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts) in packages/trae/.trae/skills/paper-workflow-orchestrator of yushui2022/MathModel-Skill.
- SKILL.md
- MATHMODEL_EDITION.json
- scripts/preflight_check.py
- scripts/prepare_output_layout.py
- scripts/quickstart_run.py
- scripts/run_all.py
- scripts/workflow_guard.py
Open the folder on GitHubat commit 7712876
Compare with similar skills
MathModel Paper Workflow Orchestrator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| MathModel Paper Workflow Orchestrator this skillyushui2022/MathModel-Skill | 454 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Nature-Style Scientific FiguresYuan1z0825/nature-skills | 47k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Scientific Figure MakingChenLiu-1996/figures4papers | 8.3k | — | ~557 | Automated safety check: Pass | Custom licence | |
| AutoMCM Math Modeling AgentRealSeaberry/AutoMCM-Pro | 257 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Academic Paper to PPTXYuan1z0825/nature-skills | 47k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Academic Figurejoshua-zyy/academic-paper-writer | 115 | — | ~816 | Automated safety check: Pass | MIT |
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Academic Paper to PPTX
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More from yushui2022/MathModel-Skill
All 10 skills in this repoModeling Paper Rubric and Model Selector
yushui2022/MathModel-Skill
Builds a scoring-aligned outline for a mathematical modeling paper and a model selection plan with baseline, improvement and validation experiments.
Modeling Code and Result Contracts
yushui2022/MathModel-Skill
Generates result-evidence contracts, tables and runnable q1 to q3 modeling code scaffolds for a math modeling paper from a model route, a data plan and cleaned data.
Formal Modeling Paper Writer
yushui2022/MathModel-Skill
Plans, drafts, audits, formats and verifies a formal mathematical-modeling paper from an evidence chain, delivering audited Markdown and a Word file with native equations.
Paper Micro-Unit Generator
yushui2022/MathModel-Skill
Repairs one failing section of a mathematical modeling paper from the repair queue, or builds a legacy or quickstart scaffold when you ask for one by name.
Authoritative Data Harvester
yushui2022/MathModel-Skill
Finds authoritative public data sources for modeling tasks, prefers official APIs and bulk downloads, and outputs a reproducible fetch and cleaning plan with citations.
Context Memory Keeper
yushui2022/MathModel-Skill
Maintains a two-layer persistent memory for a math-modeling paper workflow: long-term rules plus a short-term workbench, with finished tasks archived.
Related
Works with
Categories
Questions about MathModel Paper Workflow Orchestrator
What does MathModel Paper Workflow Orchestrator do?
Routes a full mathematical-modeling contest paper from the raw problem files through modeling, reproducible code, evidence checks and a final Word document with native equations. This skill is the single entry point for a complete contest-paper request in a mathematical modeling workflow aimed at strong models that can hold a long evidence chain, as opposed to a separate Pro mode that runs multi-agent tournaments with approval checkpoints.json file for the recommended next skill and action, treating the current files and hashes as authoritative over conversational memory.
When should I use MathModel Paper Workflow Orchestrator?
MathModel Paper Workflow Orchestrator fits situations like: starting a complete mathematical-modeling contest paper from problem files; resuming a contest paper workflow after a previous session stopped partway; checking which stage of the paper pipeline is next and what it still needs; keeping a long paper-writing workflow consistent across many steps.
How do I install MathModel Paper Workflow Orchestrator in Claude Code?
Run `npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a claude-code`. Or copy the skill folder (packages/trae/.trae/skills/paper-workflow-orchestrator in yushui2022/MathModel-Skill) into .claude/skills/paper-workflow-orchestrator in your project. Claude Code loads it when a task matches its description.
How do I install MathModel Paper Workflow Orchestrator in Codex?
Run `npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a codex`. Or copy the skill folder (packages/trae/.trae/skills/paper-workflow-orchestrator in yushui2022/MathModel-Skill) into .agents/skills/paper-workflow-orchestrator in your project. Codex loads it when a task matches its description.
Can I use MathModel Paper Workflow Orchestrator in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yushui2022/MathModel-Skill --skill paper-workflow-orchestrator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/paper-workflow-orchestrator, .gemini/skills/paper-workflow-orchestrator, .github/skills/paper-workflow-orchestrator and .opencode/skills/paper-workflow-orchestrator in your project.
What does MathModel Paper Workflow Orchestrator need to run?
Going by SKILL.md and its folder, MathModel Paper Workflow Orchestrator needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python to run the bundled preflight, workflow guard and orchestration scripts; A contest project folder laid out with a problem_files directory.
Does MathModel Paper Workflow Orchestrator access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is MathModel Paper Workflow Orchestrator safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does MathModel Paper Workflow Orchestrator use?
MathModel Paper Workflow Orchestrator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does MathModel Paper Workflow Orchestrator use?
About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to MathModel Paper Workflow Orchestrator?
Skills that share tags, products or a category with MathModel Paper Workflow Orchestrator: Nature-Style Scientific Figures (Yuan1z0825/nature-skills, 47k stars), Scientific Figure Making (ChenLiu-1996/figures4papers, 8.3k stars), AutoMCM Math Modeling Agent (RealSeaberry/AutoMCM-Pro, 257 stars) and Academic Paper to PPTX (Yuan1z0825/nature-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains MathModel Paper Workflow Orchestrator?
yushui2022 (a GitHub user) maintains it in yushui2022/MathModel-Skill, which has 454 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 7, 2026.
Source: yushui2022/MathModel-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.