What is paper-screener?

A research-paper screening tool that filters papers in two stages: first by title and abstract, then by reading the full PDF. It combines scores and creates structured summaries and a report.

Use it after paper crawling to rank papers, resolve disagreements between reviewers, summarize selected studies, and prepare literature-review material.

It helps narrow a large paper collection to relevant, higher-quality studies while keeping track of how decisions were made.

How Guo-Chenxu/paper-agent configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to Guo-Chenxu/paper-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/Guo-Chenxu/paper-agent/main/.claude/skills/paper-screener/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/Guo-Chenxu/paper-agent

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/guo-chenxu/paper-agent/paper-screener/github.svg)](https://agentmods.dev/skills/guo-chenxu/paper-agent/paper-screener)

Your own site

<a href="https://agentmods.dev/skills/guo-chenxu/paper-agent/paper-screener"><img src="https://agentmods.dev/badge/skills/guo-chenxu/paper-agent/paper-screener/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/guo-chenxu/paper-agent/paper-screener"><img src="https://agentmods.dev/badge/skills/guo-chenxu/paper-agent/paper-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,915 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00045	$0.02915
Opus 5.5	$0.00018	$0.01166
Sonnet 5.5	$0.00009	$0.00583
Haiku 4.5	$0.00005	$0.00292

Measured 2mo ago against content hash 5d12663e7dd5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

paper-screener scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/load_papers_for_screening.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/paper-screener/SKILL.md · 297 lines

How it starts

The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Paper Screener

Skill Goal

Automated two-round paper screening and structured summarization:

Round 1: Title+abstract pre-screening with 3 parallel agents for fast coarse filtering
Round 2: Full-text deep screening with 3 parallel agents reading complete PDFs
Score aggregation with arbitration when agent disagreement exceeds threshold
Structured paper summaries for high-scoring papers, generated from full-text reading
Comprehensive screening report with statistics, rankings, and traceability

When To Use

After paper crawling produces abstracts and metadata
Need to filter and rank candidate papers by quality and relevance
Want structured, full-text-based summaries of selected papers
Preparing input for literature review or research idea generation

Prerequisites

Required inputs from a prior crawl run:

./papers/abstracts/*.txt — abstract text files
./papers/metadata/papers_*.json — paper metadata records
./papers/pdfs/*.pdf — full-text PDFs (required for Round 2; download if missing)

Required Python packages:

python -m pip install requests

Scripts

Load papers for screening: ./scripts/load_papers_for_screening.py

Workflow

Step 1: Load and Prepare Papers

python .claude/skills/paper-screener/scripts/load_papers_for_screening.py \
  --abstracts-dir ./papers/abstracts \
  --metadata-dir ./papers/metadata \
  --output screening_input.json

This produces a JSON file with paper titles, abstracts, venues, years, and authors for agent scoring.

Step 2: Round 1 — Title+Abstract Pre-Screening

Purpose: Fast coarse filtering to reduce the candidate set. Scores from this round are NOT used as final quality judgments.

Spawn 3 parallel subagents, each scoring every paper independently. Each agent receives only the title and abstract.

Scoring Criteria (1–10 total):

Dimension	Points	Description
Relevance	5	Fit with the target research domain
Potential Innovation	3	Novelty indicated in the abstract
Publication Quality	2	Venue tier, citation count

Read the full file on GitHub · 297 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

scripts/load_papers_for_screening.py 5.5 KB runs code

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 297 lines · 45 tokens per session scan A 5d12663e7dd5

Subscribe to this mod's changes

paper-screener is a skill published in the GitHub repository Guo-Chenxu/paper-agent (4 stars, last pushed 2d ago), licensed Apache-2.0. It adds 45 tokens to every session and 2,915 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Research Scientific

paper-screener next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
paper-screenerGuo-Chenxu/paper-agent	Skill	4	2d ago	Apache-2.0	A	45	Claude Code
instrument-data-to-allotropeanthropics/knowledge-work-plugins	Skill	35k	2d ago	Apache-2.0	A	123	Claude Code
exploratory-data-analysisK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	83	Claude Code
matlabK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	44	Claude Code
phylogeneticsK-Dense-AI/scientific-agent-skills	Skill	56k	4d ago	MIT	A	71	Claude Code, Codex
research-engineerdavila7/claude-code-templates	Skill	33k	yesterday	MIT	A	43	Claude Code, Codex
mapping-to-snomedmaziyarpanahi/openmed	Skill	5.8k	yesterday	Apache-2.0	A	205	Claude Code

paper-agent: Skill for Claude Code