Paper Reading AssistantSAFE
🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.
Overview
🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.
e1ba289846fdOBSERVED · 2026-10-08Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| openclaw | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: paper-reading-assistant
description: "AI-assisted paper reading, PDF Q&A, and summarization workflows"
metadata:
openclaw:
emoji: "📖"
category: "research"
subcategory: "paper-review"
keywords: ["paper reading assistant", "PDF Q&A", "document understanding", "paper summarization"]
source: "wentor-research-plugins"
---
# Paper Reading Assistant
Systematic workflows for reading, annotating, and extracting insights from academic papers, including AI-assisted summarization and critical analysis techniques.
## The Three-Pass Reading Method
Srinivasan Keshav's three-pass approach provides a structured way to read papers at increasing depth:
### Pass 1: Survey (5-10 minutes)
Read only:
1. Title, abstract, and keywords
2. Introduction (first and last paragraph only)
3. Section headings (all of them)
4. Conclusion
5. Glance at figures and tables (read captions)
6. Check the reference list for familiar papers
After Pass 1, you should know:
- **Category**: Is this an empirical study, theoretical contribution, system paper, survey?
- **Context**: What related work does it build on?
- **Correctness**: Do the assumptions and claims seem reasonable?
- **Contributions**: What are the main claimed contributions?
- **Clarity**: Is the paper well-written?
**Decision**: Stop here if the paper is not relevant, or continue to Pass 2.
### Pass 2: Comprehension (30-60 minutes)
Read the full paper, but skip proofs and complex derivations:
1. Examine figures and tables carefully
2. Mark unread references for later
3. Annotate key claims, methods, and results
4. Try to summarize each section in one sentence
After Pass 2, you should be able to:
- Summarize the paper's main contribution to someone else
- Identify the key evidence supporting the claims
- List the paper's strengths and weaknesses
### Pass 3: Recreation (1-4 hours)
For papers you need to deeply understand:
1. Try to mentally re-derive the key results
2. Challenge every assumption
3. Identify implicit assumptions not stated
4. Think about how you would improve the work
5. Compare the approach to alternatives
## Structured Note-Taking Template
Use a consistent template for every paper you read:
```markdown
# Paper Notes: [Short Title]
## Metadata
- **Title**: Full title
- **Authors**: First Author et al. (Year)
- **Venue**: Conference/Journal
- **DOI/URL**: link
- **Date read**: YYYY-MM-DD
## Summary (2-3 sentences)
What does this paper do, and what are the main findings?
## Problem
What problem does this paper address? Why is it important?
## Method
How do they approach the problem? Key technical details.
## Key Results
- Result 1: ...
- Result 2: ...
- Result 3: ...
## Strengths
- Strength 1: ...
- Strength 2: ...
## Weaknesses / Limitations
- Weakness 1: ...
- Weakness 2: ...
## Questions / Things I Don't Understand
- Question 1: ...
## Relevance to My Work
How does this connect to my research? What can I use?
## Key References to Follow Up
- [Author, Year] - Why it seems relevant
```
## AI-Assisted Paper Analysis
### Summarization Prompts
Use structured prompts to extract specific information from papers:
```python
# Prompt template for paper summarization
summarize_prompt = """Read the following academic paper and provide:
1. ONE-SENTENCE SUMMARY: The core contribution in a single sentence.
2. KEY FINDINGS (3-5 bullet points):
- Finding 1 with specific numbers/results
- Finding 2 ...
3. METHODOLOGY: Describe the approach in 2-3 sentences.
4. LIMITATIONS: List 2-3 limitations acknowledged or unacknowledged.
5. RELEVANCE: How does this relate to [your research topic]?
Paper text:
{paper_text}
"""
# Prompt for critical analysis
critique_prompt = """Analyze the following paper critically:
1. VALIDITY: Are the experimental design and statistical analyses sound?
Identify any threats to internal/external validity.
2. NOVELTY: What is genuinely new? What is incremental?
3. REPRODUCIBILITY: Could you replicate this study from the description given?
What information is missing?
4. ALTERNATIVE EXPLANATIONS: Are there alternative interpretations
of the results that the authors do not consider?
5. FOLLOW-UP QUESTIONS: What would you want to investigate next?
Paper text:
{paper_text}
"""
```
### PDF Processing Pipeline
```python
import fitz # PyMuPDF
def extract_paper_text(pdf_path):
"""Extract structured text from an academic paper PDF."""
doc = fitz.open(pdf_path)
sections = []
current_section = {"heading": "Preamble", "text": ""}
for page_num, page in enumerate(doc):
blocks = page.get_text("dict")["blocks"]
for block in blocks:
if "lines" not in block:
continue
for line in block["lines"]:
text = "".join(span["text"] for span in line["spans"])
font_size = max(span["size"] for span in line["spans"])
is_bold = any("Bold" in span.get("font", "") for span in line["spans"])
# Heuristic: detect section headings
if is_bold and font_size > 11 and len(text.strip()) < 80:
if current_section["text"].strip():
sections.append(current_section)
current_section = {"heading": text.strip(), "text": ""}
else:
current_section["text"] += text + " "
if current_section["text"].strip():
sections.append(current_section)
doc.close()
return sections
# Extract and display
sections = extract_paper_text("paper.pdf")
for s in sections:
print(f"\n## {s['heading']}")
print(s['text'][:200] + "...")
```
### Batch Paper Processing
```python
import os
import json
def process_paper_batch(pdf_dir, output_file):
"""Process a batch of papers and save structured notes."""
results = []
for filename in os.listdir(pdf_dir):
if not filename.endswith(".pdf"):
continue
pdf_path = os.path.jTrust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
e1ba289846fdfull audit observations/trust-audit/skill/brycewang-stanford__paper-reading-assistant.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-08 | e1ba289846fd | SAFE | B | 89 | first audit |
Questions
What does the Paper Reading Assistant skill do?
🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.
Is Paper Reading Assistant safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Paper Reading Assistant access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does Paper Reading Assistant work with?
Its documentation mentions openclaw. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (e1ba289846fd), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.