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scalingx666-ai

Awesome Paper MCP

get_paper_text

Download a paper by arXiv ID, DOI, or backend ID and return readable text from arXiv, PubMed, bioRxiv, Crossref, OpenAlex, or OpenReview, with optional character truncation.

Instructions

Download a paper and return its readable text.

Args: paper_id: arXiv id, DOI, or backend-specific id. source: Backend to use. arxiv (default) supports arXiv ids; multisearch supports arXiv/PubMed/bioRxiv/medRxiv/Crossref/OpenAlex/...; openreview_classic exports OpenReview PDFs. max_chars: Truncate the returned text to this many characters.

Input Schema

NameRequiredDescriptionDefault
sourceNoarxiv
paper_idYes
max_charsNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the full burden. It does disclose that a network download happens, that text is truncated at max_chars, and that backend choice changes which identifiers resolve — genuinely useful behavior. It says nothing about permissions, rate limits, failure modes, or whether truncated output is signaled, which is a real gap for an unannotated tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded purpose sentence followed by a compact Args block; every line carries information and nothing is padded. The docstring formatting is slightly awkward as agent-facing prose but costs no comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the return value needs no explanation, and all three parameters are documented. What's missing is behavioral context an agent would want before calling: how errors surface for an invalid id, whether truncation is indicated in the response, and any cost or latency implications of downloading full papers.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate, and it largely does: paper_id is described as accepting arXiv ids, DOIs, or backend-specific ids, and source enumerates three concrete backend values that the schema itself does not declare as an enum. max_chars is explained as a truncation limit. It falls short of 5 because it doesn't clarify which id forms each backend accepts.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific verb (download) plus resource (paper) and the returned artifact (readable text), which distinguishes it from the metadata-oriented get_paper. It never explicitly names the sibling it replaces, so an agent must infer the split from the return type alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The source argument description implicitly guides selection by naming which backends handle which id types, which is useful context for choosing a call. However, there is no explicit statement of when to use this versus get_paper or search_papers, and no prerequisites or failure conditions are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.