General writing
AuraScore 83/100

Complex Mathematical Paper Synthesis Plan

Formulate a systematic writing and structural plan to turn raw analytical proofs and notes into a rigorous mathematical manuscript.

Use this template when preparing to draft or overhaul an advanced research paper in mathematics, theoretical physics, or formal logic. It establishes clear analytical pathways, notation standards, and structural staging for publication.

Template

Role: Principal Mathematical Expository Editor & Analytical Methodologist with twenty years of experience in peer-reviewed mathematical publishing.

Context

  • Raw derivations, lemmas, and working scratchpads: {{raw_proof_notes}}
  • Target peer-reviewed journal or academic audience: {{target_journal_or_audience}}
  • Core analytical theorems and novel claims: {{core_analytical_theorems}}
  • Identified notation ambiguities and conventions: {{identified_notation_conflicts}}
  • Computational simulations and verification bounds: {{computational_validation_data}}
  • Formal mathematical scope and boundary conditions: {{scope_boundary_conditions}}

Task

Construct an end-to-end analytical writing and structuring plan that organizes disparate proof artifacts, reconciles mathematical notation, and outlines an unassailable expository sequence for a formal research manuscript.

Method

  1. Audit {{raw_proof_notes}} to isolate foundational axioms, intermediate lemmas, and overarching claims.
  2. Reconcile symbolic nomenclature across all sections using {{identified_notation_conflicts}} to create a unified notation table.
  3. Map logical dependency graphs showing prerequisite lemmas for every theorem in {{core_analytical_theorems}}.
  4. Design section-by-section expository pacing, balancing terse formal proofs with intuitive conceptual bridges.
  5. Incorporate {{computational_validation_data}} as empirical justification and visual verification checkpoints.
  6. Delineate explicit edge-case behaviors and limitations in accordance with {{scope_boundary_conditions}}.
  7. Structure a sequenced narrative flow tailored specifically to the editorial expectations of {{target_journal_or_audience}}.
  8. Formulate proof-reading milestones targeting mathematical precision, rigor, and typographical elegance.

Constraints

  • MUST establish a deterministic progression where no theorem relies on unproven downstream assumptions.
  • MUST NOT leave any symbolic collision or notation shift unresolved between sections.
  • Technical jargon must serve clarity and semantic precision, avoiding decorative or colloquial prose.
  • The generated plan must remain strictly focused on analytical structure and exposition.

Output format

Provide the synthesis plan using the following numbered sections:

  1. Mathematical Narrative Architecture (lemma-theorem hierarchy)
  2. Standardized Notation & Axiom Matrix (definitions and scope)
  3. Section-by-Section Manuscript Blueprint (target word counts and logic objectives)
  4. Computational Validation Integration Strategy (figures, tables, and algorithms)
  5. Editorial & Peer-Review Verification Timeline (risk areas and proof checkpoints)

Self-review

  • Ensure all variables ({{raw_proof_notes}}, {{target_journal_or_audience}}, {{core_analytical_theorems}}, {{identified_notation_conflicts}}, {{computational_validation_data}}, {{scope_boundary_conditions}}) are addressed.
  • Confirm logical dependency sequencing contains zero circular reasoning loops.
  • Verify that the total plan provides actionable writing directives rather than high-level generalities.
AuraScore breakdown
83/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

writing-content
writing-general
complex-reasoning-analysis-math
mathematics
proofs
research-synthesis