publication
Build and review a Chinese XeLaTeX mathematical-modeling paper from a fixed selected result, evidence freeze, and formal execution manifest.
Skill by SoFarSoGoodya
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/sofarsogoodya-publication
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/publication
What's inside
- Skill name
publication- Description
- Build and review a Chinese XeLaTeX mathematical-modeling paper from a fixed selected result, evidence freeze, and formal execution manifest. Use for final paper narrative, result-backed figures, submission PDFs, or publication checks; do not use to change algorithms, samples, metrics, units, or human approval.
- License
- MIT
- Instructions
- 28 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Publication Read the selected-result record, evidence freeze, formal run manifest, current rule config, and available human adoption facts before drafting. Stop with a science revision when the run identity, metric value/definition/unit, sample set, aggregation, adopted claim, or rule binding conflicts. Display-only changes such as final size, typography, color, marker, linestyle, hatch, legend, and caption may proceed without recomputing a Metric. Create a short `paper_plan.md` that states what each section answers, the frozen evidence it uses, the mathematical or visual role, and the conclusion boundary. Write one coherent TeX source rather than concatenating agent fragments. Repeated result values must come from `generated/results.tex`, not manual transcription. Use execution-owned data and scripts for data figures. Match final insertion width, provide a non-color encoding, and draw intervals only when the run defines them. When only an original real image exists without data or a script, disclose that it cannot be redrawn. Never present a conceptual illustration as measured data. Build the electronic target with XeLaTeX, then check citations, placeholders, anonymity, critical numbers, page/size rules, metadata, embedded fonts, and the text layer. Rasterize every page and inspect all of them. Compilation alone leaves `visual_review_pending`; `review_ready` requires explicit page-complete visual notes and is not human approval. Use `mathmodel_agent.publication.build_publication(case_root, request)` for the deterministic pipeline. See `docs/modules/publication.md` for the request fields, rule configuration, CLI hook, and exact commands.
From SoFarSoGoodya/mathmodel-weave, MIT.
More from SoFarSoGoodya/mathmodel-weave
- 0.595score
execution
SoFarSoGoodya
Run a local mathematical experiment through the MathModel runtime and package traceable observations, metrics, checks, and figures.
SkillAFreshness: A★ 2Claude Code +9 - 0.587score
coordinator
SoFarSoGoodya
Coordinate a bounded mathematical-modeling case through runtime RESULT.json handoffs and human decisions.
SkillAFreshness: A★ 2Claude Code +9 - 0.554score
evidence
SoFarSoGoodya
Intake modeling problem files and curate research evidence with faithful source text, targeted verification, pins, and freezes.
SkillBFreshness: B★ 2Claude Code +9 - 0.549score
review
SoFarSoGoodya
Independently review mathematical-modeling candidates, experiments, comparisons, or fusions from fixed selected material.
SkillBFreshness: B★ 2Claude Code +9 - 0.546score
exploration
SoFarSoGoodya
Develop independently reasoned mathematical-modeling candidates and fixed comparison material for an approved case.
SkillBFreshness: B★ 2Claude Code +9
Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 2, 2026 (27 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/SoFarSoGoodya/mathmodel-weave
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from SoFarSoGoodya
- 0.595score
execution
SoFarSoGoodya
Run a local mathematical experiment through the MathModel runtime and package traceable observations, metrics, checks, and figures.
SkillAFreshness: A★ 2Claude Code +9 - 0.587score
coordinator
SoFarSoGoodya
Coordinate a bounded mathematical-modeling case through runtime RESULT.json handoffs and human decisions.
SkillAFreshness: A★ 2Claude Code +9 - 0.554score
evidence
SoFarSoGoodya
Intake modeling problem files and curate research evidence with faithful source text, targeted verification, pins, and freezes.
SkillBFreshness: B★ 2Claude Code +9 - 0.549score
review
SoFarSoGoodya
Independently review mathematical-modeling candidates, experiments, comparisons, or fusions from fixed selected material.
SkillBFreshness: B★ 2Claude Code +9 - 0.546score
exploration
SoFarSoGoodya
Develop independently reasoned mathematical-modeling candidates and fixed comparison material for an approved case.
SkillBFreshness: B★ 2Claude Code +9
Cite this page
publication skill. Agent Mart. https://agentmart.dev/skills/sofarsogoodya-publication (last updated 2026-10-24)