NSFC Abstract Writer
huangwb8/ChineseResearchLaTeX
Writes Chinese and English abstracts for NSFC grant applications, with a recommended title and five alternatives, within set character limits.
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.
Install Paper Micro-Unit Generator
$ npx skills add yushui2022/MathModel-Skill --skill paper-micro-unit-generator -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-micro-unit-generator --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-micro-unit-generator .claude/skills/paper-micro-unit-generator && 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-micro-unit-generator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-micro-unit-generator into .claude/skills/paper-micro-unit-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-micro-unit-generator", 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-micro-unit-generatorType 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-micro-unit-generator -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-micro-unit-generator --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-micro-unit-generator .agents/skills/paper-micro-unit-generator && 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-micro-unit-generator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-micro-unit-generator into .agents/skills/paper-micro-unit-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-micro-unit-generator", 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-micro-unit-generator -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-micro-unit-generator --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-micro-unit-generator .cursor/skills/paper-micro-unit-generator && 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-micro-unit-generator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-micro-unit-generator into .cursor/skills/paper-micro-unit-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-micro-unit-generator", 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-micro-unit-generator--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-micro-unit-generator -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yushui2022/MathModel-Skill paper-micro-unit-generator --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-micro-unit-generator .gemini/skills/paper-micro-unit-generator && 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-micro-unit-generator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-micro-unit-generator into .gemini/skills/paper-micro-unit-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-micro-unit-generator", 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-micro-unit-generatorInstalls 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-micro-unit-generator -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-micro-unit-generator .github/skills/paper-micro-unit-generator && 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-micro-unit-generator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-micro-unit-generator into .github/skills/paper-micro-unit-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-micro-unit-generator", 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-micro-unit-generator -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-micro-unit-generator --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-micro-unit-generator .opencode/skills/paper-micro-unit-generator && 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-micro-unit-generator" agent skill from https://github.com/yushui2022/MathModel-Skill/tree/standard/packages/trae/.trae/skills/paper-micro-unit-generator into .opencode/skills/paper-micro-unit-generator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paper-micro-unit-generator", 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-micro-unit-generator- GitHub stars
- 454
- Token cost
- ~1.1k tokens
- SKILL.md length
- 430 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- MIT
At a glance
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.
- Works in 7 steps: Read… → Select only queued micro-repair items.… → Read the affected section draft and only… → …
- A paper section keeps failing its audit after repeated changed attempts
- SKILL.md covers Entry Check, Formal Repair Mode, Repair Rules and Legacy Mode, plus 2 more sections
- Runs Python scripts from its folder; calls python
What it does
This skill is a narrow repair step inside a larger paper-writing workflow. After a section has failed its audit twice, it reads the writing plan, the authoring state, the draft audit and the repair queue, picks only the items marked for micro-repair, and writes concrete replacement text for that one claim or paragraph into a file under paper_output/drafts/repairs.
It then applies the replacement while keeping valid headings, equations, figure and table numbers, citations and evidence markers, re-runs the section validator and hands control back to paper-formal-writer or paper-workflow-orchestrator. It never assembles the final manuscript or the Word file, never invents data or citations, and stops and reports if the same failure survives a third changed attempt. The folder also ships generate_all_offline.py, merge.py and a micro-unit library reference.
When your agent uses it
- A paper section keeps failing its audit after repeated changed attempts
- An entry in repair_queue.json is marked for micro-repair
- You explicitly want the legacy or quickstart paper scaffold
Example prompts
- “The results section failed its audit twice; repair the queued micro-repair item without touching other sections.”
- “Read paper_output/qa/repair_queue.json and fix only the entries marked micro-repair.”
- “Generate the old quickstart scaffold for this paper, I want the legacy layout.”
Requirements
- The paper-formal-writer and paper-workflow-orchestrator skills with their paper_output files
- Python to run the workflow guard and validation scripts
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Read paper_output/plan/writing_plan.json, paper_output/context/authoring_state.json, paper_output/qa/draft_audit.json, and…
- Select only queued micro-repair items. Keep the issue ID, section, failure category, expected evidence, and attempt count intact.
- Read the affected section draft and only the evidence needed by that issue. Do not rewrite unrelated sections.
- Write repair material to paper_output/drafts/repairs/.md. The material must contain concrete replacement text, its target location, and…
- Apply the replacement to the queued section draft. Preserve valid headings, equations, figure/table identifiers, citations, and evidence…
- Re-run the section audit
- Return to $paper-formal-writer or $paper-workflow-orchestrator. This skill must not assemble the formal manuscript or generate Word.
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 2 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
Paper Micro-Unit Generator loads about 1.1k tokens when it runs, and up to ~7.8k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 430 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). 430 words, ~1,141 tokens.
Download SKILL.mdSave it as
.claude/skills/paper-micro-unit-generator/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- paper-micro-unit-generator
- description
- Repair a repeatedly failing Standard paper section from repair_queue.json, or generate an explicitly requested legacy/quickstart scaffold. Do not use it as the formal paper writer.
Paper Micro-Unit Generator
Use this skill only for local repair or an explicitly requested legacy scaffold. paper-formal-writer remains the sole formal author and the only producer of paper_output/final_paper_source.md and paper_output/final_paper.docx.
Entry Check
For formal repair, run:
python .trae/skills/paper-workflow-orchestrator/scripts/workflow_guard.py --skill paper-micro-unit-generatorContinue only when S0-S6 pass and paper_output/qa/repair_queue.json contains at least one item whose strategy is micro-repair. Do not create a repair queue manually to bypass the two-failure threshold.
Legacy and quickstart modes are installation or old-model scaffolds. They do not satisfy S7 and do not require the formal repair queue.
Formal Repair Mode
- Read
paper_output/plan/writing_plan.json,paper_output/context/authoring_state.json,paper_output/qa/draft_audit.json, andpaper_output/qa/repair_queue.json. - Select only queued
micro-repairitems. Keep the issue ID, section, failure category, expected evidence, and attempt count intact. - Read the affected section draft and only the evidence needed by that issue. Do not rewrite unrelated sections.
- Write repair material to
paper_output/drafts/repairs/<issue-id>.md. The material must contain concrete replacement text, its target location, and any required evidence marker. - Apply the replacement to the queued section draft. Preserve valid headings, equations, figure/table identifiers, citations, and evidence markers.
- Re-run the section audit:
python .trae/skills/paper-formal-writer/scripts/validate_authoring.py --section <section-id>- Return to
$paper-formal-writeror$paper-workflow-orchestrator. This skill must not assemble the formal manuscript or generate Word.
If the same blocking category reaches the third changed attempt, respect authoring_state.status = BLOCKED. Report the evidence or requirement causing the failure and suggest Lite as a user decision; never switch editions automatically.
Show full SKILL.md (203 more words)Show less
Repair Rules
- Repair the failed claim or paragraph, not the whole paper.
- Use only computed values and paths present in the current evidence chain.
- Preserve
<!-- mathmodel-evidence: ... -->markers until deterministic assembly removes them. - Do not invent data, citations, completed experiments, or successful validation.
- Do not expose workflow language in paper prose.
- Do not renumber existing figure, table, equation, or bibliography references.
- A repair is complete only after
validate_authoring.py --sectionreturns PASS.
Legacy Mode
The old command names remain available. With no arguments they write only to paper_output/drafts/legacy/:
python .trae/skills/paper-micro-unit-generator/scripts/generate_all_offline.py
python .trae/skills/paper-micro-unit-generator/scripts/merge.pyExpected outputs:
paper_output/drafts/legacy/micro_units/*.txt
paper_output/drafts/legacy/generate_log.json
paper_output/drafts/legacy/legacy_scaffold.md
paper_output/drafts/legacy/legacy_scaffold.docx
paper_output/drafts/legacy/legacy_ref_check.mdtasks.json is required only for this legacy batch path. The merge is deterministic and preserves existing reference numbers.
For the built-in smoke test, the orchestrator passes --output-root paper_output/quickstart --stem quickstart_scaffold; all smoke-test files stay under paper_output/quickstart/.
Never write final_paper.md, final_paper_source.md, final_paper.docx, or similarly formal names from legacy/quickstart mode.
Template Library
Read references/micro-unit-library.md only when a queued repair needs a fine-grained paragraph/sentence pattern or when the user explicitly requests legacy scaffolding. Do not load the full 200+ template library for ordinary section writing.
Handoff
After a formal repair, run workflow status and update persistent context:
python .trae/skills/paper-workflow-orchestrator/scripts/workflow_guard.py --status
python .trae/skills/context-memory-keeper/scripts/update_workflow_memory.pyThe guard report is authoritative if memory and current artifacts disagree.
Read the persistent snapshot at paper_output/context/workflow_memory.json before resuming a repair.
© 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 3 other files (scripts, references) in packages/trae/.trae/skills/paper-micro-unit-generator of yushui2022/MathModel-Skill.
- SKILL.md
- references/micro-unit-library.md
- scripts/generate_all_offline.py
- scripts/merge.py
Open the folder on GitHubat commit 7712876
Compare with similar skills
Paper Micro-Unit Generator 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 |
|---|---|---|---|---|---|---|
| Paper Micro-Unit Generator this skillyushui2022/MathModel-Skill | 454 | — | ~1.1k | Automated safety check: Pass | MIT | |
| NSFC Abstract Writerhuangwb8/ChineseResearchLaTeX | 2.9k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature-Style Scientific FiguresYuan1z0825/nature-skills | 47k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Citation ManagementK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.9k | Automated safety check: Notes | MIT | |
| Autonomous Researchfedericodeponte/opendraft | 507 | — | ~8.2k | Automated safety check: Pass | Apache-2.0 | |
| Math Modeling Competition WorkflowXiaoMaColtAI/math-modeling-skill | 1.9k | — | ~1.2k | Automated safety check: Pass | None |
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Yuan1z0825/nature-skills
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Citation Management
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Finds papers in OpenAlex, PubMed and Google Scholar, turns DOIs, PMIDs and arXiv IDs into clean BibTeX, and validates citations for a manuscript or thesis.
Autonomous Research
federicodeponte/opendraft
An 18-agent pipeline that turns one topic line into a drafted research paper, literature review, or thesis chapter.
Math Modeling Competition Workflow
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Three-role workflow for math modeling contests: problem analysis, code and results, then a paper, with independent subagent checks at each stage gate.
- Official
Hugging Face Paper Publisher
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Indexes research papers on the Hugging Face Hub from arXiv, links them to models and datasets, claims authorship and generates markdown research articles from templates.
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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.
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Finds authoritative public data sources for modeling tasks, prefers official APIs and bulk downloads, and outputs a reproducible fetch and cleaning plan with citations.
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Maintains a two-layer persistent memory for a math-modeling paper workflow: long-term rules plus a short-term workbench, with finished tasks archived.
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Related
Works with
Categories
Questions about Paper Micro-Unit Generator
What does Paper Micro-Unit Generator do?
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. This skill is a narrow repair step inside a larger paper-writing workflow. After a section has failed its audit twice, it reads the writing plan, the authoring state, the draft audit and the repair queue, picks only the items marked for micro-repair, and writes concrete replacement text for that one claim or paragraph into a file under paper_output/drafts/repairs.
When should I use Paper Micro-Unit Generator?
Paper Micro-Unit Generator fits situations like: A paper section keeps failing its audit after repeated changed attempts; an entry in repair_queue.json is marked for micro-repair; you explicitly want the legacy or quickstart paper scaffold.
How do I install Paper Micro-Unit Generator in Claude Code?
Run `npx skills add yushui2022/MathModel-Skill --skill paper-micro-unit-generator -a claude-code`. Or copy the skill folder (packages/trae/.trae/skills/paper-micro-unit-generator in yushui2022/MathModel-Skill) into .claude/skills/paper-micro-unit-generator in your project. Claude Code loads it when a task matches its description.
How do I install Paper Micro-Unit Generator in Codex?
Run `npx skills add yushui2022/MathModel-Skill --skill paper-micro-unit-generator -a codex`. Or copy the skill folder (packages/trae/.trae/skills/paper-micro-unit-generator in yushui2022/MathModel-Skill) into .agents/skills/paper-micro-unit-generator in your project. Codex loads it when a task matches its description.
Can I use Paper Micro-Unit Generator 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-micro-unit-generator -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-micro-unit-generator, .gemini/skills/paper-micro-unit-generator, .github/skills/paper-micro-unit-generator and .opencode/skills/paper-micro-unit-generator in your project.
What does Paper Micro-Unit Generator need to run?
Going by SKILL.md and its folder, Paper Micro-Unit Generator needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: The paper-formal-writer and paper-workflow-orchestrator skills with their paper_output files; Python to run the workflow guard and validation scripts.
Does Paper Micro-Unit Generator 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 Paper Micro-Unit Generator 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 Paper Micro-Unit Generator use?
Paper Micro-Unit Generator 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 Paper Micro-Unit Generator use?
About 1.1k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.7k tokens, read only when the agent opens those files.
What are the alternatives to Paper Micro-Unit Generator?
Skills that share tags, products or a category with Paper Micro-Unit Generator: NSFC Abstract Writer (huangwb8/ChineseResearchLaTeX, 2.9k stars), Nature-Style Scientific Figures (Yuan1z0825/nature-skills, 47k stars), Citation Management (K-Dense-AI/claude-scientific-writer, 2.4k stars) and Autonomous Research (federicodeponte/opendraft, 507 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Paper Micro-Unit Generator?
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.