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 --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.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 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 .trae/skills/paper-formal-writer/scripts/build_paper_outline.py
python .trae/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 .trae/skills/paper-formal-writer/scripts/assemble_sections.py
python .trae/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 .trae/skills/paper-formal-writer/scripts/validate_authoring.py --final
python .trae/skills/paper-formal-writer/scripts/format_formal_docx.py
S8 Format And Render Gate
Run:
python .trae/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 .trae/skills/paper-workflow-orchestrator/scripts/workflow_guard.py --status
python .trae/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.