What is scholarfetch AGENTS.md?

Instructions for ScholarFetch, a research environment for finding and organizing academic papers. It treats papers, abstracts, full text, references, and authors as connected parts of a literature set.

It supports literature searches, finding papers by author or DOI, following references, reviewing abstracts or articles, and exporting a compact research set.

It helps an agent narrow a broad search while keeping only useful papers in a named collection. Abstracts can be used for quick screening before reading full text.

How laibniz/scholarfetch configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to laibniz/scholarfetch. 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/laibniz/scholarfetch/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/laibniz/scholarfetch

Made for: Codex, OpenCode.

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/instructions/laibniz/scholarfetch/agents-md/github.svg)](https://agentmods.dev/instructions/laibniz/scholarfetch/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/laibniz/scholarfetch/agents-md"><img src="https://agentmods.dev/badge/instructions/laibniz/scholarfetch/agents-md/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/instructions/laibniz/scholarfetch/agents-md"><img src="https://agentmods.dev/badge/instructions/laibniz/scholarfetch/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 998 This file is loaded in full into every session.

When invoked 998 The same file — it is already loaded in full.

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	$0.00998	$0.00998
Opus 5.5	$0.00399	$0.00399
Sonnet 5.5	$0.00200	$0.00200
Haiku 4.5	$0.00100	$0.00100

Measured 2mo ago against content hash c219780158db, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

scholarfetch AGENTS.md 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.

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.

AGENTS.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ScholarFetch Agent Guide

ScholarFetch is a stateful research environment for agents.

Use it to build and refine a literature set over multiple MCP calls, not just to fetch isolated papers.

What The Agent Should Optimize For

start broad, then narrow aggressively
preserve only high-value papers in a named collection
use abstracts for cheap triage
use full text only for shortlisted papers
expand references and authors only when they improve topic coverage
export a compact artifact for downstream synthesis

Mental Model

ScholarFetch exposes a research tree:

topic -> papers
paper -> abstract
paper -> full text
paper -> references
paper -> authors
author -> papers

The collection parameter is the agent's working memory inside one MCP server process.

Primary Tool Roles

Discovery

scholarfetch_search
scholarfetch_doi_lookup
scholarfetch_author_candidates

Use these to establish seed nodes.

Traversal

scholarfetch_author_papers
scholarfetch_references

Use these to move through the literature graph.

Reading

scholarfetch_abstract
scholarfetch_article_text

Use these to decide whether a paper deserves inclusion.

Curation

scholarfetch_saved_add
scholarfetch_saved_list
scholarfetch_saved_remove
scholarfetch_saved_clear
scholarfetch_saved_export

Use these to keep a coherent reading list and hand off the result.

Recommended Agent Loop

Run scholarfetch_search with a topic query.
Save obviously relevant papers with scholarfetch_saved_add.
For ambiguous authors, run scholarfetch_author_candidates.
Expand the strongest author nodes with scholarfetch_author_papers.
Read abstracts with scholarfetch_abstract.
Read full text with scholarfetch_article_text only for shortlisted papers.
Expand references with scholarfetch_references when a paper looks central or foundational.
Revisit the saved list with scholarfetch_saved_list.
Remove weak papers with scholarfetch_saved_remove.
Export with scholarfetch_saved_export.

Read the full file on GitHub · 156 lines

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 · 156 lines · 998 tokens per session scan A c219780158db

Subscribe to this mod's changes

scholarfetch AGENTS.md is an instructions file published in the GitHub repository laibniz/scholarfetch (1 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 998 tokens to every session, about $0.0040 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.

Learning and teaching Research

scholarfetch AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
scholarfetch AGENTS.mdlaibniz/scholarfetch	Instructions file	1	7mo ago	Apache-2.0	A	998	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

scholarfetch: Instructions file for Codex