Use when the user wants to write, structure, or revise academic paper sections, improve notation consistency, or refine figures and tables. Triggers on phrases like "write the abstract", "structure the methods", "improve this section", "notation consistency", "figure refinement", or "paper structure".
SkillScore68Maintained
Automatic
◆Writing & Editing pack
Last verified 8/21/2026
What it changes
Passed 15 of 22 test cases with the skill, and 12 of 22 without it.
Without skill55%
With skill68%
Checks it passed that the model alone missed
Calculates annual cost breakdowns for graduate research assistant stipends and tuition support
Captures specifications including exact data source, takeaway message, and hard constraints like font size
Concludes the paragraph by stating explicitly how the current work addresses the limitation of prior methods
and 1 more in the full report
4 fixed11 passed either way6 still failing1 broke
Pass-rate lift
+14 pp
Tokens
+40%
Agent turns
0%
Response time
-10%
Model gemini-3.6-flashMeasured 8/21/2026v115 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 4
Prompt
We want to update Figure 2 in our paper. What step should be performed before generating or editing the plot code?
What was checked, without and with the skill
Checked
Without skill
With skill
Captures specifications including exact data source, takeaway message, and hard constraints like font size
Missed
Passed
case-19 · gemini-3.6-flash · 8/21/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md112 linessingle file
Academic Paper Writing Methodology
You are helping a researcher write or revise an academic paper. Follow this methodology to produce clear, precise, publication-ready text.
Core Principles
Precision over elegance — every sentence must be verifiable against code or data
Claims require evidence — never state a result without pointing to its source
Notation consistency — define once, use identically everywhere
Conciseness — remove words that don't add information
Section-Specific Guidance
Abstract
Structure: problem → approach → key result → significance
Include 1-2 concrete numbers (dataset size, main metric improvement)
Every number must be traceable to a specific experiment
No citations in abstract unless venue requires it
Introduction
Paragraph 1: Problem and why it matters (societal/practical motivation)
Paragraph 2: Why existing approaches are insufficient (gap)
Paragraph 3: Your approach and why it addresses the gap
Paragraph 4: Contributions list (concrete, falsifiable claims)
Each contribution must map to a section that provides evidence
Related Work
Organize by theme/approach, not chronologically
For each group: what they do, what's missing, how your work differs
Be fair: acknowledge strengths of prior work, don't strawman
End each paragraph with how your work addresses the limitation
Methods
Define all notation in a single place (notation table or first-use definitions)
Each method component should be independently understandable
Include enough detail that someone could reimplement from the paper
Cross-reference equations with corresponding code
Experiments
Dataset: size, splits, preprocessing (cite or describe collection)