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paper-orchestra

EZMM writer-stage adapter for the vendored PaperOrchestra skill pack. Use by default during pipeline/04-paper-writing for outline-first paper drafting, literature-review planning, section writing, and refinement discipline. The adapter maps EZMM runtime artifacts to PaperOrchestra-style inputs, runs PaperOrchestra-first writing automatically, and returns EZMM-compatible paper.md.

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설치 방법 보기

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  • SKILL.md7.4 KB

SKILL.md(원문)

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paper-orchestra adapter for EZ Math Model

This is the EZMM-facing adapter for the vendored upstream PaperOrchestra pack at external/paper-orchestra/. It lets the EZMM writer call PaperOrchestra's writing skills without changing EZMM's contest-paper contract.

Upstream source: https://github.com/Ar9av/PaperOrchestra

Paper citation: Song et al., "PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing", arXiv:2604.05018, 2026.

When writer calls this

Load this adapter in pipeline/04-paper-writing before drafting paper.md. Use it to create a structured writing workspace, generate or refresh a paper outline, organize literature-review tasks, draft the body, and run a refinement pass.

Do not use this adapter to bypass EZMM hard rules. The final paper.md must still satisfy prompts/writer.md, references/roles/writer-guide.md, and pipeline/05-quality-audit.md.

Source roots

All paths below are relative to skills/ez-math-model/.

PurposePath
EZMM adaptertools/paper-orchestra/SKILL.md
Vendored upstream packexternal/paper-orchestra/
Upstream orchestratorexternal/paper-orchestra/skills/paper-orchestra/SKILL.md
Upstream outline agentexternal/paper-orchestra/skills/outline-agent/SKILL.md
Upstream literature agentexternal/paper-orchestra/skills/literature-review-agent/SKILL.md
Upstream section writerexternal/paper-orchestra/skills/section-writing-agent/SKILL.md
Upstream refinement agentexternal/paper-orchestra/skills/content-refinement-agent/SKILL.md
Upstream shared writing checksexternal/paper-orchestra/skills/shared/writing_quality_check.md

When running upstream helper scripts, set the working directory to external/paper-orchestra/ so upstream examples like python skills/paper-orchestra/scripts/validate_inputs.py ... resolve correctly.

Default mode: PaperOrchestra-first writing

The writer runs PaperOrchestra-first by default. Do not wait for a separate PaperOrchestra request. Build the PaperOrchestra workspace automatically from EZMM runtime artifacts, run the upstream outline, literature, section-writing, and refinement protocol as far as the local inputs and tools allow, then bridge the result back to EZMM's required runtime/{task_id}/paper.md.

When a usable LaTeX template and TeX toolchain are available or can be safely scaffolded, also produce the upstream-style package under runtime/{task_id}/paper_orchestra/final/. The EZMM-compatible paper.md remains mandatory because downstream quality audit and packaging consume it.

Create a local workspace:

runtime/{task_id}/paper_orchestra/
├── inputs/
│   ├── idea.md
│   ├── experimental_log.md
│   ├── conference_guidelines.md
│   └── figures/
├── outline.json
├── refs/
├── drafts/
│   ├── paper.tex
│   └── paper.md
├── refinement/
│   └── worklog.json
├── final/
│   ├── paper.tex
│   └── paper.pdf
└── adapter_report.md

Map EZMM inputs into PaperOrchestra-style inputs:

PaperOrchestra inputEZMM source
idea.mdproblem.md, intake.json, modeling_plan.md, and the intended contribution of each quesN
experimental_log.mdexecution_log.md, src/*.py final print blocks, `results/*.csv
conference_guidelines.mdcontest name, language, run_mode, section requirements from templates/chapter_outline.toml, plus EZMM no-bullet and no-leakage rules
inputs/figures/copies or references to figures/*.png with usable_in_paper=true

The adapter report must record which EZMM files were consumed, which accepted figures must appear in the paper, and whether any PaperOrchestra sub-step was degraded or skipped.

Writing workflow

  1. Read upstream outline-agent/SKILL.md and use its schema discipline to produce paper_orchestra/outline.json. For EZMM, section_plan must map to the contest sections in templates/chapter_outline.toml.
  2. Read upstream literature-review-agent/SKILL.md for search, verification, deduplication, and citation-pool discipline. Prefer EZMM tools/scholar/SKILL.md or tools/paper_search/SKILL.md for actual metadata retrieval, because those tools already follow the EZMM env and setup policy.
  3. Read upstream section-writing-agent/SKILL.md for single-pass global coherence, table construction, figure-text alignment, and citation-key discipline. Prefer the upstream LaTeX draft path when the workspace has a usable template; then convert or mirror the accepted content into EZMM Markdown. If LaTeX inputs or tools are unavailable, adapt LaTeX-only instructions directly to Markdown:
    • figures stay as ![描述](figures/name.png);
    • tables stay as Markdown tables unless paper_*.md template requires otherwise;
    • formulas stay in pandoc-compatible $...$ / $$...$$;
    • do not introduce LaTeX preamble, \section, \cite, or BibTeX in paper.md.
  4. Read upstream content-refinement-agent/SKILL.md and run refinement by default unless the draft is blocked by missing factual inputs. Accept a revision only when it improves correctness, figure-text binding, citation integration, or clarity without weakening EZMM constraints.
  5. Write the final Markdown to runtime/{task_id}/paper.md only after the adapter's self-check passes.

Upstream LaTeX package

Run the upstream orchestrator automatically when the required workspace/inputs/template.tex and workspace/inputs/conference_guidelines.md can be supplied from EZMM templates or local contest metadata. Use external/paper-orchestra/skills/paper-orchestra/SKILL.md unchanged for that sub-run and write outputs under paper_orchestra/final/.

If the full LaTeX route is not runnable, do not ask the user. Record the reason in adapter_report.md, continue with the Markdown adaptation path, and keep the same PaperOrchestra outline/literature/section/refinement discipline.

Required self-check before returning to writer

Before this adapter hands control back to the writer stage, confirm:

  • paper_orchestra/outline.json exists or adapter_report.md explains why it was skipped.
  • adapter_report.md records whether the full upstream LaTeX route ran or which missing input/tool caused an automatic Markdown adaptation.
  • Every chart_manifest.json entry with status=accepted and usable_in_paper=true is listed in adapter_report.md.
  • paper.md references only figures allowed by EZMM chart manifest.
  • No PaperOrchestra workspace paths, upstream script paths, runtime/, adapter_report.md, or outline.json leak into the paper body.
  • Citations are unique and compatible with EZMM's {[^N] ...} protocol.
  • Any skipped PaperOrchestra sub-step is recorded as a quality-audit note.

Licensing note

The vendored upstream pack is MIT licensed. Keep the upstream LICENSE, CITATION.cff, and README under external/paper-orchestra/, and cite PaperOrchestra when its workflow materially shapes the final paper.

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같은 저장소의 스킬

Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.md). TRIGGER when the user says "aggregate my agent logs for paper writing", "extract experiments from my coding agent history", "prepare PaperOrchestra inputs from my cache", "turn my agent logs into a paper", mentions a folder or directory they want to use as the basis for a paper, or wants to run PaperOrchestra but only has scattered agent experiment histories rather than structured inputs. Run this BEFORE paper-orchestra. Also called automatically by paper-orchestra when workspace/inputs/idea.md or workspace/inputs/experimental_log.md are missing.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

woodfishhhh/EZ_math_model432026년 7월 28일 업데이트

Use when EZ_math_model model selection is unclear after the modeling decision tree, the problem spans multiple domains, or modeler needs several candidate approaches before writing modeling_plan.md.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

woodfishhhh/EZ_math_model432026년 7월 28일 업데이트

Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules. Maintains a worklog and snapshots each iteration so revert is real, not symbolic. TRIGGER when the orchestrator delegates Step 5 or when the user asks to "refine the draft", "iterate on the paper", or "run peer review on this paper".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

woodfishhhh/EZ_math_model432026년 7월 28일 업데이트

dataset

무료

公开数据集发现入口。覆盖 Kaggle / UCI / HuggingFace / 天池。题目要求"自行 查找数据"或"补充外部数据"时启用;附件已含数据时**不调用**。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

woodfishhhh/EZ_math_model432026년 7월 28일 업데이트

Use when EZ_math_model runs in multi or hybrid mode and has two or more independent subtasks that can be assigned to subagents without shared files, shared state, or dataflow dependencies.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

woodfishhhh/EZ_math_model432026년 7월 28일 업데이트

docx

무료

Use when EZ_math_model needs to convert paper.md to paper.docx, read a DOCX problem statement, preserve equations and tables, or package a modeling report as a Word document.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

woodfishhhh/EZ_math_model432026년 7월 28일 업데이트

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