literature-review-sprint

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Guide a CS or AI PhD student through a focused literature review sprint that produces a ranked paper map, notes, gaps, and next actions. Use this skill whenever the user needs to survey a topic, prepare related work, check whether an idea is novel, catch up on a field, read papers before a meeting, or turn a pile of papers into an organized research direction.

2installs

Sourcea-green-hand-jack/phd-skills

Added on2026-04-25

NPX Install

npx skill4agent add a-green-hand-jack/phd-skills literature-review-sprint

SKILL.md Content

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Literature Review Sprint

Purpose

Turn "I need to read more papers" into a bounded, systematic review. This skill follows the handbook's literature review advice: search systematically, prioritize high-quality sources, assess institution/year/venue/impact, summarize key ideas and limitations, and stay current with top conferences and recent papers.

The output is a usable map of the field, not a long undigested bibliography.

When to Use

User is starting a new topic
User wants to verify novelty of an idea
User is writing related work
User has many papers and no structure
User needs a reading plan before an advisor or group meeting

Workflow

Stage 1: Define the Review Question

Ask for:

Topic or problem
Target field or venue family
Purpose: novelty check, related work writing, method comparison, dataset search, or general catch-up
Deadline and available reading time
Existing seed papers, if any

Force a narrow review question. "Diffusion models" is too broad; "diffusion policies for robot manipulation under distribution shift" is workable.

Stage 2: Build the Search Plan

Create search queries for:

Google Scholar / Semantic Scholar
arXiv
Top venue proceedings in the field
Hugging Face Papers or similar recent-paper hubs for ML topics
References and citations of 2-3 seed papers

For current topics, prioritize the last 2 years first, then trace backward to canonical papers.

Stage 3: Triage Papers

Classify papers into:

```
Core
```
: must read carefully
```
Context
```
: skim for framing or related work
```
Maybe
```
: keep if time remains
```
Reject
```
: irrelevant, low quality, or superseded

Assess each paper using:

Institution or lab
Year
Venue
Citation/impact signal
Method relevance
Evaluation relevance
Clear limitation or gap

Stage 4: Extract Notes

For each core paper, produce compact notes:

One-sentence contribution
Problem setting
Key method
Dataset/task
Baselines
Main result
Limitation
How it relates to the user's project

Keep notes short enough that they remain searchable.

Stage 5: Synthesize the Map

Create a field map organized by axes that matter for the topic, such as:

Method families
Dataset/task families
Assumptions
Evaluation metrics
Failure modes
Open gaps

Name 3-5 concrete gaps or tensions. Separate real gaps from "I have not read enough yet."

Stage 6: Produce the Artifact

Save to

~/phd-log/literature/YYYY-MM-DD-[topic].md

.

markdown

# Literature Review Sprint — [Topic]

## Review question
[Specific question]

## Search plan
- Queries:
- Venues / sources:
- Seed papers:

## Paper triage
| Title | Year | Venue | Category | Why |
|---|---:|---|---|---|

## Core paper notes
### [Paper title]
- Contribution:
- Setting:
- Method:
- Evaluation:
- Main result:
- Limitation:
- Relevance:

## Field map
- Method families:
- Evaluation setups:
- Common assumptions:
- Failure modes:

## Candidate gaps
1. [gap + evidence]
2. [gap + evidence]
3. [gap + evidence]

## Next actions
- [ ] Read:
- [ ] Reproduce/check:
- [ ] Ask:
- [ ] Update idea/related work:

Tone

Be structured and skeptical. The user should leave with a smaller, clearer reading list and a sense of what matters.

What Not to Do

Do not produce generic paper summaries without synthesis.
Do not treat citation count as the only quality signal.
Do not over-prioritize old canonical papers when the user needs current trends.
Do not let the user claim novelty before checking recent top venues and arXiv.