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chan4kum

ArXivLens MCP

by chan4kum

Find Code Repositories

find_code_repositories

Find open-source GitHub repositories that implement or reference a specific arXiv paper. Provide the arXiv ID to locate code implementations.

Instructions

Discover open-source GitHub repositories implementing or referencing an arXiv paper.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoOptional title of the paper to enhance repository discovery.
arxiv_idYesThe arXiv ID of the paper.
max_resultsNoMaximum number of repositories to return (default: 5).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses the core behavior—searching GitHub for repositories tied to an arXiv paper—and 'discover' implies a read-only operation. However, it does not mention details like whether results are limited to open-source only (though it says open-source) or any search constraints beyond the schema.

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

Conciseness5/5

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

The description is a single, front-loaded sentence with no filler. It conveys the tool's scope and purpose efficiently, and every word contributes to understanding what the tool does.

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 simple scope, fully described parameters, and the presence of an output schema, the description is largely complete. The only minor gap is the absence of explicit guidance on when to invoke this tool relative to the sibling tools, but the core call pattern is clear.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already fully documents all three parameters. The description adds no additional parameter-level meaning beyond the schema, so the baseline score of 3 is appropriate.

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 states a specific action ('Discover'), a specific resource ('open-source GitHub repositories'), and a precise selection criterion ('implementing or referencing an arXiv paper'). This clearly distinguishes the tool from siblings like search_arxiv, which finds papers, and get_paper_details, which retrieves paper details.

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 description implies the tool should be used when an arXiv ID is already known and code repositories are needed, but it does not explicitly say when to prefer this over siblings or when not to use it. No alternatives or exclusions are named, leaving the routing decision to inference.

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