process-new-papers

A batch workflow for processing PDF files placed directly in the papers/ directory. It sends each unprocessed PDF to paper-reader, using parallel workers when available.

In plain words
What is it for?
Use it to process all PDFs in the collection's root papers directory, either in parallel or one at a time.
Why use it?
It avoids opening and processing each newly added PDF by hand.

Skill for Claude CodeCodex

Part of the research-papers plugin — 28 skills shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/ctoth/research-papers-plugin/process-new-papers
Any agent
npx skills add ctoth/research-papers-plugin --skill process-new-papers
Clone the repo
git clone --depth 1 https://github.com/ctoth/research-papers-plugin

Made for: Claude Code, Codex.

Or install research-papers, the plugin that ships this one along with the rest of its 28 skills.

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,343 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.01343
Opus 5 $0.00032 $0.00672
Sonnet 5 $0.00013 $0.00269
Haiku 4.5 $0.00006 $0.00134

Measured 3d ago against content hash c85196e6dc63, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

process-new-papers 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 3d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/pdf_adoption.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.

plugins/research-papers/skills/process-new-papers/SKILL.md · 130 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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.

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.

  1. 3d ago First seen · 130 lines · 65 tokens per session scan A c85196e6dc63

Subscribe to this mod's changes

process-new-papers is a skill published in the GitHub repository ctoth/research-papers-plugin (31 stars, last pushed 9d ago), with no licence file. It adds 65 tokens to every session and 1,343 once invoked, about $0.0003 per session on Opus 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 2026-08-30.

Related

Other skills, from other repositories

excalidraw-diagram

Generate Excalidraw diagrams from text content. Supports three output modes - Obsidian (.md), Standard (.excalidraw), and Animated (.excalidraw with animation order). Triggers on "Excalidraw", "diagram", "standard excalidraw", "animate".

breferrari/obsidian-mind · 67 tokens

mermaid-visualizer

Transform text content into professional Mermaid diagrams for presentations and documentation. Use when users ask to visualize concepts, create flowcharts, or make diagrams from text. Supports process flows, system architectures, comparisons, mindmaps, and more with built-in syntax error prevention.

breferrari/obsidian-mind · 57 tokens

qmd

Search the vault using QMD semantic search. Use PROACTIVELY before reading files. Preference order: (1) MCP tools — mcpqmdquery, mcpqmdget, mcpqmdmultiget, mcpqmdstatus — if they appear in your tool menu, use them first; (2) CLI qmd --index ... as fallback; (3) Grep/Glob only when QMD is not installed. Trigger…

breferrari/obsidian-mind · 142 tokens

obsidian-cli

Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. Use when the user asks to interact with their…

breferrari/obsidian-mind · 102 tokens

nsfc-budget

当用户明确要求“写/生成 NSFC 预算说明书”“写预算说明”“生成 budget.tex / budget.pdf”“写国自然预算 justification”时使用。基于用户标书正文或补充材料,输出一份可提交的预算说明书 LaTeX 项目并渲染 budget.pdf。若用户未指定工作目录,必须暂停并先要求其指定。⚠️ 不适用:用户只是想了解预算原则;用户仅要预算表数字而不写说明书;或用户是 2026 青年 A/B/C 默认包干制且无需预算说明书的场景。.

huangwb8/ChineseResearchLaTeX · 138 tokens

nsfc-ref-alignment

检查 NSFC 标书正文引用与参考文献的一致性与真实性风险(只读):核查 bibkey 是否存在、BibTeX 字段与 DOI 等格式问题,并生成结构化输入供宿主 AI 逐条评估“正文表述是否真的在引用该文献”;默认仅输出审核报告,不直接修改标书或 .bib(除非用户明确要求)。.

huangwb8/ChineseResearchLaTeX · 90 tokens