research-taste-developer

📁 ghostscientist/skills 📅 Jan 28, 2026
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npx skills add https://github.com/ghostscientist/skills --skill research-taste-developer

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Skill 文档

Research Taste Developer

Research taste is the ability to distinguish work that matters from work that doesn’t – before the community tells you. This skill helps you develop that instinct.

What is Research Taste?

It’s the intuition that lets experienced researchers:

  • Pick problems that turn out to be important
  • Know when an idea is “close” vs. “far” from working
  • Recognize a good result even with imperfect execution
  • Predict which papers will be remembered in 5 years

Taste isn’t magic – it’s pattern recognition from deep exposure. This skill accelerates that exposure.

Process

Phase 1: Analyze the Field

Pick a specific subfield. We’ll study what “good” looks like there.

Questions to investigate:

  1. What are the 10 most-cited papers of the last 5 years?
  2. What are the 5 papers experts say “changed how we think”?
  3. What are the best papers from top venues (NeurIPS, ICML, CVPR, etc.)?
  4. What got awards? What got invited talks?

For each landmark paper, analyze:

  • What was the state before this paper?
  • What’s the single core insight?
  • What specifically made people cite it?
  • Was it obvious in hindsight?

Phase 2: Pattern Recognition

Look for what the great papers have in common:

The Patterns of Impact:

1. The New Primitive

Papers that introduce a building block others build on.

  • Examples: Attention mechanism, ResNet skip connections, Dropout
  • Pattern: Simple idea, surprisingly general applicability
  • Why it works: Reduces friction for future work

2. The Surprising Connection

Papers that link two previously separate areas.

  • Examples: VAE (variational inference + neural nets), NeRF (neural nets + ray marching)
  • Pattern: “X, but for Y” where the combination is non-obvious
  • Why it works: Cross-pollinates communities

3. The Scaling Insight

Papers showing that scale changes qualitative behavior.

  • Examples: GPT-3, Chinchilla
  • Pattern: What everyone “knew” was wrong at sufficient scale
  • Why it works: Forces field to update beliefs

4. The Rigorous Foundation

Papers that formalize what was previously folklore.

  • Examples: Theoretical convergence proofs, generalization bounds
  • Pattern: Makes hand-wavy intuitions precise
  • Why it works: Enables confident building

5. The Elegant Solution

Papers that solve a problem far more simply than expected.

  • Examples: Simple baseline papers, “X is all you need”
  • Pattern: Previous solutions were overcomplicated
  • Why it works: Shifts field’s complexity assumptions

Phase 3: Anti-Patterns

Learn to recognize work that won’t age well:

The Incremental Treadmill:

  • Pattern: +0.5% on benchmark with architectural tweak
  • Why it fails: No one remembers or uses it
  • Exception: When it reveals something fundamental

The Method Mashing:

  • Pattern: “We combine A, B, C, and D”
  • Why it fails: No insight about why the combination works
  • Exception: When combination reveals unexpected interaction

The Benchmark Overfitter:

  • Pattern: Method that works only on specific benchmarks
  • Why it fails: Doesn’t transfer, forgotten when benchmarks change
  • Exception: When it exposes benchmark weaknesses

The Complexity Monster:

  • Pattern: Works but requires 47 hyperparameters and 3 loss terms
  • Why it fails: No one can reproduce or build on it
  • Exception: Rarely

The Solution Without a Problem:

  • Pattern: Novel method without compelling use case
  • Why it fails: “Interesting but why?”
  • Exception: When use case emerges later (rare)

Phase 4: Develop Your Own Taste

Exercise 1: Prediction Game Before reading a paper, predict based on title/abstract:

  • Will this paper be cited >100 times in 5 years?
  • Write down your prediction and reasoning
  • Track your accuracy over time
  • Analyze where your predictions went wrong

Exercise 2: Explain the Gap For any two papers in citation count:

  • Paper A: 2000 citations
  • Paper B: 50 citations (same venue, same year)
  • What explains the difference?
  • Write a paragraph explanation

Exercise 3: The Time Machine Pick a highly-cited paper. Go back to when it was published:

  • What was the state of the field?
  • Would you have recognized its importance?
  • What signals would you have looked for?

Exercise 4: Design a Hit Given current state of a field:

  • What’s the most important open problem?
  • What would a “great paper” on this look like?
  • What would make people cite it?

Phase 5: Meta-Principles

What top researchers seem to do differently:

Problem Selection:

  • Work on problems that are “ready” (pieces exist, no one assembled them)
  • Avoid problems that are stuck for fundamental reasons
  • Pick problems where you have unfair advantages

Execution Taste:

  • Know when to stop polishing (diminishing returns)
  • Know when result is “strong enough” to share
  • Prefer simple-that-works over complex-that-works-slightly-better

Communication Taste:

  • Lead with the insight, not the method
  • Make contribution obvious in first 2 minutes
  • Anticipate and address likely objections

Portfolio Taste:

  • Mix safe and risky projects
  • Build a coherent research identity
  • Create compound interest (each paper enables the next)

Output: Taste Development Report

# Research Taste Analysis: [Field/Subfield]

## Landmark Paper Analysis

### [Paper 1 Title] ([Year])
- **Pre-existing state:** [What was true before]
- **Core insight:** [One sentence]
- **Why it's cited:** [Specific reason]
- **Pattern type:** [New Primitive / Connection / etc.]

### [Paper 2 Title]
[Same structure]

## Pattern Distribution
In this subfield, highly-cited papers tend to be:
- [X]% New Primitives
- [Y]% Surprising Connections
- [Z]% Other

## Anti-Pattern Warnings
The following patterns are common but don't lead to impact:
1. [Anti-pattern common in this field]
2. [Another one]

## Taste Heuristics for [Field]
When evaluating a paper in this field, ask:
1. [Field-specific question that distinguishes good from meh]
2. [Another one]
3. [Another one]

## Current Opportunities
Based on this analysis, promising directions seem to be:
1. [Direction 1]: [Why it's ripe]
2. [Direction 2]: [Why it's ripe]

## Your Taste Development Exercises
1. [Specific exercise for this field]
2. [Another one]

The Ultimate Test

You have good taste when:

  • You’re bored by work others find impressive (correctly predicting it won’t matter)
  • You’re excited by work others overlook (correctly predicting it will matter)
  • Your intuitions about importance are calibrated with reality
  • You can articulate why something is good, not just that it is

This takes years. But deliberate practice – not just reading, but analyzing – accelerates it dramatically.