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paper-workflow-orchestrator

paper-workflow-orchestrator

github.com/yushui2022Documents45839 installsUpdated 4d ago
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About paper-workflow-orchestrator

paper-workflow-orchestrator is a skill for coordinating end-to-end mathematical modeling competition papers. It guides agents through staged checks and artifact-based status reports, requiring validated evidence before formal writing.

Key features

  1. 01Check input files and runtime dependencies
  2. 02Guide work through S0–S8 stages
  3. 03Route to the next skill using status reports
  4. 04Validate modeling results and evidence
  5. 05Check paper formatting and rendered output

Use cases

  1. 01Run a paper task from contest input through delivery
  2. 02Resume an interrupted task at its current stage
  3. 03Validate model-result evidence before formal writing

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/yushui2022/mathmodel-skill --skill paper-workflow-orchestrator

After installing, type/paper-workflow-orchestratorin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

MATHMODEL_EDITION.json
agents/
openai.yaml
scripts/
preflight_check.py
prepare_output_layout.py
quickstart_run.py
run_all.py
workflow_guard.py

Details

From the project README

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 .claude/skills/paper-workflow-orchestrator/scripts/preflight_check.py
python .claude/skills/paper-workflow-orchestrator/scripts/workflow_guard.py --status

Read 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.json
  • paper_output/input_manifest.json
  • paper_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.json
  • paper_output/plan/rubric_alignment.json
  • paper_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 .claude/skills/quality-assurance-auditor/scripts/evidence_gate.py --mode official

Do not enter formal writing until paper_output/qa/evidence_gate_report.json is PASS and all recorded inputs are still fresh.

S7 Adaptive Formal Writing

Use $paper-formal-writer as the sole formal author:

python .claude/skills/paper-formal-writer/scripts/build_paper_outline.py
python .claude/skills/paper-formal-writer/scripts/prepare_authoring.py --mode auto

Normal 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 .claude/skills/paper-formal-writer/scripts/assemble_sections.py
python .claude/skills/paper-formal-writer/scripts/validate_authoring.py --assembled

The Agent must then globally revise the full assembly into paper_output/final_paper_source.md; a copy-only promotion is rejected. Finish with:

python .claude/skills/paper-formal-writer/scripts/validate_authoring.py --final
python .claude/skills/paper-formal-writer/scripts/format_formal_docx.py
S8 Format And Render Gate

Run:

python .claude/skills/paper-formal-writer/scripts/check_paper_format.py --render required

Delivery 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.json

Legacy 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 .claude/skills/paper-workflow-orchestrator/scripts/workflow_guard.py --status
python .claude/skills/context-memory-keeper/scripts/update_workflow_memory.py

Read the guard report, current stage contracts, and paper_output/context/workflow_memory.json; continue from the first failing stage instead of replaying completed work.

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