paper-mcp: Agent for Claude Code

.claude/agents/paper-summarizer.md

paper-summarizer is an agent for Claude Code from Friedemann12/paper-mcp. It costs 62 tokens per session (306 once invoked), scanned A, original, no licence file.

Un agente que resume artículos de arXiv, un repositorio donde investigadores comparten trabajos científicos, y responde preguntas sobre su contenido usando versiones guardadas en Markdown.

In plain words
What is it for?
Sirve para resumir artículos de arXiv y responder preguntas concretas sobre ellos a partir de su texto almacenado.
Why use it?
Permite consultar artículos científicos largos sin cargar todo su texto en la conversación principal. También mantiene las preguntas centradas en el contenido del artículo.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is Friedemann12/paper-mcp's own configuration. It tells Claude Code how to work on paper-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything paper-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Friedemann12/paper-mcp. 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/Friedemann12/paper-mcp/main/.claude/agents/paper-summarizer.md
Clone the repo
git clone --depth 1 https://github.com/Friedemann12/paper-mcp

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.

agentmods badge for paper-summarizer

README.md
[![agentmods](https://agentmods.dev/badge/agents/friedemann12/paper-mcp/paper-summarizer/github.svg)](https://agentmods.dev/agents/friedemann12/paper-mcp/paper-summarizer)
Your own site
<a href="https://agentmods.dev/agents/friedemann12/paper-mcp/paper-summarizer"><img src="https://agentmods.dev/badge/agents/friedemann12/paper-mcp/paper-summarizer/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.

agentmods 80×15 button for paper-summarizer

Your own site · 80×15
<a href="https://agentmods.dev/agents/friedemann12/paper-mcp/paper-summarizer"><img src="https://agentmods.dev/badge/agents/friedemann12/paper-mcp/paper-summarizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 306 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 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 5.1 $0.00062 $0.00306
Opus 5 $0.00031 $0.00153
Sonnet 5 $0.00012 $0.00061
Haiku 4.5 $0.00006 $0.00031

Measured 8d ago against content hash 7182e63478d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

paper-summarizer 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 8d ago.

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/agents/paper-summarizer.md · 29 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

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. 8d ago First seen · 29 lines · 62 tokens per session scan A 7182e63478d2

Subscribe to this mod's changes

paper-summarizer is an agent published in the GitHub repository Friedemann12/paper-mcp (0 stars, last pushed 2mo ago), with no licence file. It adds 62 tokens to every session and 306 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 2026-08-31.

Related

Other agents, from other repositories

editor

Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].

pedrohcgs/claude-code-my-workflow · 64 tokens

Geoprocessing Specialist

ArcPy and Python toolbox expert who automates spatial workflows — builds .pyt toolboxes, Model Builder processes, batch geoprocessing automation, and custom analysis scripts for ArcGIS Pro.

SHAdd0WTAka/Zen-Ai-Pentest · 45 tokens

research-scout

Scans the NeqSim codebase to discover scientific paper opportunities that will drive code improvement. Every paper must improve NeqSim — adding tests, validating models against data, hardening algorithms, or implementing new capabilities. Produces ranked, actionable topics that feed into the planner agent.

equinor/neqsim · 61 tokens

mathodology-problem-analyst

Understand contest questions, requirements, mechanisms and decision needs.

sweetcornna/mathodology · 20 tokens

astronomical-instrumentation-scientist

Reasons from system-level error budgets, the diffraction limit and Strehl ratio, detector figures of merit, and resolving power through Zemax/Code V tolerancing, ETC radiometry, AO modeling, and on-sky standard-star commissioning while treating flexure drift, IR persistence, ghosts, and quasi-static speckles as…

K-Dense-AI/scientific-agents · 78 tokens

eic_agent

Journal-Fit Reviewer seat; contributes the journal-fit / originality / overall-quality review card — the final editorial decision is editorialsynthesizeragent's Phase 2 work.

GGbond-bo/MemOmics-Agent · 38 tokens