/paper-planning

name: paper-planning
description: "Guides pre-writing planning for academic papers with 4 structured steps: story design (task-challenge-insight-contribution-advantage), experiment planning (comparisons + ablations), figure design (pipeline + teaser), and 4-week timeline management. Includes counterintuitive planning tactics (write a mock rejection letter to identify weaknesses before writing, narrow before broad claims, design ablations first). Use when: user wants to plan a paper before writing, design story/contributions, plan experiments, create figure sketches, set a writing timeline, or write a pre-emptive rejection letter for planning purposes. Do NOT use for actual writing (use paper-writing), running experiments (use experiment-pipeline), self-reviewing a finished draft (use paper-review), or finding research problems (use research-ideation)."
allowed-tools: "write_file edit_file read_file think_tool"
metadata:
  author: EvoScientist
  version: '1.0.0'
  tags: [core, research, writing, academic-writing, experiment-design]

Paper Planning

A structured approach to planning academic papers before writing begins. Covers four key activities: Story design, Experiment planning, Figure design, and Timeline management.

When to Use This Skill

> If you don't yet have an idea, use the `research-ideation` skill first to find a problem and design a solution.

• User wants to plan a paper before writing
• User asks about structuring a paper's story or contributions
• User needs to plan experiments (comparisons, ablations)
• User wants to design pipeline figures or teaser figures
• User asks about writing timelines or submission schedules

Planning Overview

Paper planning follows four steps, ideally completed **before** writing begins:

Step 1: Story Design     → What is the narrative? What are the contributions?
Step 2: Experiment Plan   → What experiments prove our claims?
Step 3: Figure Design     → How do we visually communicate the method?
Step 4: Timeline          → When does each section get written?

Counterintuitive Planning First

Prioritize these counterintuitive rules before regular planning:

1. **Write your rejection letter first**: Draft the top-5 likely rejection comments ("limited novelty", "missing baseline", "not robust", etc.), then plan experiments that directly preempt each one. 2. **Narrow claim before broad claim**: Define the smallest defensible core claim first. Expand only after evidence is strong. Over-broad claims fail review more often than narrow strong claims. 3. **Design ablations before polishing method text**: If a module cannot be ablated cleanly, its contribution claim is weak. 4. **Allocate compute to stress tests, not only benchmarks**: A single convincing stress-test figure often contributes more than multiple small benchmark gains. 5. **Plan a fallback narrative now**: If SOTA gain is marginal, predefine a secondary value proposition (efficiency, robustness, fewer assumptions, wider applicability).

See [references/counterintuitive-planning.md](references/counterintuitive-planning.md)

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Step 1: Story Design

The "story" is the logical narrative that connects the problem, insight, method, and results.

Reverse Engineering the Story

Work backwards to build the story:

1. **What is the technical problem?** — The specific challenge that existing methods cannot solve well 2. **What are our contributions?** — The concrete technical novelties 3. **What are the benefits and new insights?** — What advantages does our approach provide? 4. **How do we lead into the challenge?** — How to frame the task and previous methods to naturally arrive at the challenge

Then write forward: Task → Previous methods → Challenge → Our contributions → Advantages

Core Elements to Define

Before writing any section, clearly articulate:

| Element | Question | Example | |---------|----------|---------| | Task | What problem does this paper address? | "Real-time 3D scene reconstruction" | | Challenge | Why can't existing methods solve it well? | "Cannot handle dynamic objects efficiently" | | Insight | What key observation drives our approach? | "Motion patterns are temporally sparse" | | Contribution | What do we propose? | "Sparse temporal attention for dynamic regions" | | Advantage | Why is our approach better? | "Reduces computation while preserving quality" |

Starting Point: Pipeline Figure Sketch

> Start by drawing a pipeline figure sketch. This forces you to clarify the overall method before writing.

The pipeline figure sketch serves as the paper's visual backbone:

• Draw it before writing anything
• It reveals whether the method is clear enough to explain
• It identifies the novel modules vs. standard components
• It determines subsection structure for the Method section

See [references/story-design.md](references/story-design.md)

---

Step 2: Experiment Planning

Plan experiments **before** writing to avoid discovering gaps late.

Two Categories of Experiments

**Comparison Experiments** — Prove our method is better:

• Which baseline methods to compare against?
• Which datasets and metrics?
• What is the evaluation protocol?

**Ablation Studies** — Prove each module is effective:

• Part 1: One big table showing impact of core contributions
• Part 2: Several small tables for design choices and hyperparameters

Planning Checklist

• [ ] List all comparison baselines (recent, relevant, SOTA)
• [ ] Define evaluation metrics (standard for the task)
• [ ] Identify datasets (standard benchmarks + challenging demos)
• [ ] List ablation configurations (remove each core component)
• [ ] Plan design-choice tables (hyperparameters, input quality, alternatives)
• [ ] Plan demo scenarios (challenging data to showcase upper limit)

See [references/experiment-planning.md](references/experiment-planning.md)

Experiment Plan Template

Use the template at [assets/experiment-plan-template.md](assets/experiment-plan-template