Agent skill

paper-planning

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).

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Install this agent skill to your Project

npx add-skill https://github.com/EvoScientist/EvoSkills/tree/main/skills/paper-planning

Metadata

Additional technical details for this skill

tags
core research writing academic-writing experiment-design
author
EvoScientist
version
1.0.0

SKILL.md

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


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


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

Experiment Plan Template

Use the template at assets/experiment-plan-template.md to organize your experiment plan.


Step 3: Figure Design

The pipeline figure is for highlighting novelty, not for making readers understand. The Method text is what makes readers understand.

Pipeline Figure Principles

  • Highlight novelty: The pipeline figure showcases what is new, not just the workflow
  • Differentiate from prior work: The figure must look different from previous methods
  • Novel modules stand out: If the overall pipeline is standard, zoom in on novel modules
  • Focus on clarity of the novel parts; standard components can be simplified

Teaser Figure

The teaser (usually Figure 1) shows the key result at a glance:

  • Place it at the top of the first page
  • Should be immediately compelling
  • Reference it from the Introduction

Visual Quality Matters

Visual polish directly influences review outcomes. See references/figure-design.md for the full visual quality guide (pipeline figures, tables, typography)


Step 4: Timeline

4-Week Countdown

Start writing at least 1 month before the deadline.

Week Tasks
4 weeks before 1. Organize story (core contribution, module motivations). 2. List comparison experiments and ablation studies. 3. Write Introduction first draft.
3 weeks before 1. Finalize the pipeline figure sketch. 2. Write Method first draft (use \todo{} for unsettled details). Deadline: give Introduction + Method draft to advisor.
2 weeks before Write first drafts of Experiments, Abstract, Related Work.
Last week Revise paper, polish pipeline figure and teaser, run demos.

Critical: By the end of Week 3, you must send the Introduction and Method drafts to your advisor — otherwise the advisor likely will not have enough time to finish reviewing the paper.

See references/timeline-4week.md for the detailed schedule and progress tracking template.


Handoff to Writing

When planning is complete, pass these artifacts to paper-writing:

Artifact Source Step Used By
Story summary (task → challenge → insight → contribution → advantage) Step 1 Introduction
Module Motivation Mapping table Step 1 Method subsections
Experiment plan (comparisons + ablations + demos) Step 2 Experiments section
Pipeline figure sketch Step 1 / Step 3 Method overview + Figure 2
Claim-to-experiment mapping Step 2 Abstract, Introduction, Experiments
Fallback narrative (if planned) Counterintuitive Rule 5 Introduction / Conclusion pivot
Rejection-risk table Counterintuitive Rule 1 Self-review prioritization

Reference Navigation

Topic Reference File When to Use
Story design story-design.md Starting a new paper
Experiment planning experiment-planning.md Before running experiments
Timeline timeline-4week.md Setting up a writing schedule
Figure design figure-design.md Designing pipeline/teaser figures
Experiment plan template experiment-plan-template.md Creating a structured experiment plan
Counterintuitive strategy counterintuitive-planning.md Increasing acceptance odds with non-obvious planning choices

Handoff to Presentation

If preparing a conference talk or slide deck, the academic-slides skill guides slide creation from your planning artifacts — including translating your story design and pipeline figure into presentation structure.

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EvoScientist/EvoSkills

paper-writing

Guides writing academic papers section by section using an 11-step workflow with LaTeX templates and counterintuitive writing tactics. Covers Abstract, Introduction, Method, Experiments, Related Work, Conclusion, and Supplementary. Use when: user asks to write or draft a paper section, needs LaTeX templates, wants to improve academic writing quality, optimize novelty framing, or mentions 'write introduction', 'draft method', 'paper writing'. Do NOT use for pre-submission review (use paper-review), experiment execution (use experiment-pipeline), or paper planning/story design (use paper-planning).

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evo-memory

Manages persistent research memory across ideation and experimentation cycles. Maintains two stores: Ideation Memory M_I (feasible/unsuccessful directions) and Experimentation Memory M_E (reusable strategies for data processing, model training, architecture, debugging). Three evolution mechanisms: IDE (after idea-tournament), IVE (after experiment failure — classifies failures as implementation vs fundamental), ESE (after experiment success — extracts reusable strategies). Use when: updating memory after completing idea tournaments or experiment pipelines, classifying why a method failed (implementation vs fundamental failure), starting a new research cycle needing prior knowledge, user mentions 'update memory', 'classify failure', 'what worked before', 'research history', 'evolution'. Do NOT use for running experiments (use experiment-pipeline), debugging experiment code (use experiment-craft), or generating ideas (use idea-tournament).

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paper-navigator

End-to-end academic paper workflow: disambiguate queries, discover papers (search, citation traversal, recommendations, arXiv monitoring, trending, GitHub search), evaluate (TLDR, citations, code, SOTA), read with structured analysis (3-level strategy), and organize into literature maps or reports. Use when: finding papers, reading a paper, related work, literature survey, citation analysis, research trends, SOTA results, datasets, or literature reports. Do NOT use for writing a literature review section (use paper-writing), comparing research ideas (use idea-tournament), or planning paper structure (use paper-planning).

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paper-review

Guides self-review of YOUR OWN academic paper before submission with adversarial stress-testing. Core method: 5-aspect checklist (contribution sufficiency, writing clarity, results quality, testing completeness, method design), counterintuitive protocol (reject-first simulation, delete unsupported claims, score trust, promote limitations, attack novelty), reverse-outlining, and figure/table quality checks. Use when: user wants to self-review or self-check their own paper draft before submission, stress-test their claims, prepare for reviewer criticism, or mentions 'self-review', 'check my draft', 'is my paper ready'. Do NOT use for writing a peer review of someone else's paper, and do NOT use after receiving actual reviews (use paper-rebuttal instead).

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EvoScientist/EvoSkills

experiment-craft

Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.

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EvoScientist/EvoSkills

experiment-pipeline

Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments to run (use paper-planning).

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