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paper_read

Extract text content from academic paper PDFs using identifiers from arXiv, PubMed, bioRxiv, medRxiv, IACR, Semantic Scholar, or CrossRef sources.

Instructions

Read and extract text content from academic paper PDFs from multiple sources.

Input Constraints:

  • searcher: Required, must be one of: arxiv, pubmed, biorxiv, medrxiv, iacr, semantic, crossref

  • paper_id: Required, 1-200 characters, cannot be empty

Example:

arXiv

paper_read({"searcher": "arxiv", "paper_id": "2106.12345", "save_path": "./downloads"}) # paper_id is arXiv ID.

PubMed

paper_read({"searcher": "pubmed", "paper_id": "32790614", "save_path": "./downloads"}) # paper_id is PubMed ID (PMID).

bioRxiv

paper_read({"searcher": "biorxiv", "paper_id": "10.1101/2020.01.01.123456", "save_path": "./downloads"}) # paper_id is bioRxiv DOI.

medRxiv

paper_read({"searcher": "medrxiv", "paper_id": "10.1101/2020.01.01.123456", "save_path": "./downloads"}) # paper_id is medRxiv DOI.

IACR

paper_read({"searcher": "iacr", "paper_id": "2009/101", "save_path": "./downloads"}) # paper_id is IACR paper ID.

Semantic Scholar

paper_read({"searcher": "semantic", "paper_id": "DOI:10.18653/v1/N18-3011", "save_path": "./downloads"}) where paper_id: Semantic Scholar paper ID, Paper identifier in one of the following formats: - Semantic Scholar ID (e.g., "649def34f8be52c8b66281af98ae884c09aef38b") - DOI: (e.g., "DOI:10.18653/v1/N18-3011") - ARXIV: (e.g., "ARXIV:2106.15928") - MAG: (e.g., "MAG:112218234") - ACL: (e.g., "ACL:W12-3903") - PMID: (e.g., "PMID:19872477") - PMCID: (e.g., "PMCID:2323736") - URL: (e.g., "URL:https://arxiv.org/abs/2106.15928v1")

CrossRef

paper_read({"searcher": "crossref", "paper_id": "10.1038/s41586-020-2649-2", "save_path": "./downloads"}) # paper_id is DOI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searcherYes
paper_idYesThe unique identifier of the paper to read (format depends on searcher)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the tool's behavior (reading and extracting text from PDFs) and includes detailed input constraints and examples, but it does not disclose other behavioral traits like error handling, rate limits, authentication needs, or what happens if extraction fails. The description adds value but lacks comprehensive behavioral context.

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

Conciseness3/5

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

The description is appropriately front-loaded with the core purpose, but it includes lengthy examples and formatting that could be condensed. While informative, the structure with bullet points and code blocks is somewhat verbose, reducing efficiency. Every sentence earns its place, but it could be more streamlined.

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

Completeness4/5

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

Given the tool's complexity (multiple sources with different ID formats), the description is quite complete, with detailed examples and input constraints. Since an output schema exists, the description does not need to explain return values. However, it lacks information on error cases or performance limits, leaving minor gaps.

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

Parameters5/5

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

Schema description coverage is 50% (only 'paper_id' has a description), but the description compensates fully by providing extensive parameter semantics. It explains the meaning of 'searcher' (listing valid sources) and 'paper_id' (with format details and examples for each searcher), adding significant value beyond the input schema.

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

Purpose5/5

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

The description clearly states the tool's purpose as 'Read and extract text content from academic paper PDFs from multiple sources,' which is a specific verb (read/extract) applied to a specific resource (academic paper PDFs). It distinguishes from sibling tools 'paper_download' and 'paper_search' by focusing on content extraction rather than downloading or searching.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool (for reading/extracting text from academic papers) and implies alternatives through sibling tool names, but it does not explicitly state when to choose this tool over 'paper_download' or 'paper_search.' The examples show specific use cases for different sources, which helps guide usage.

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

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