Skip to main content
Glama

load_paper

Load a local LaTeX paper to construct its theorem dependency graph, enabling exploration of theorems and their relationships.

Instructions

Load a local LaTeX paper and build its theorem graph.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
Install Server

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action and outcome but does not disclose whether the graph is returned or stored, whether a previous loaded paper is replaced, whether there are side effects, or any other operational consequences. An agent is left to guess what happens after invocation.

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?

A single sentence that is front-loaded with the action and resource and contains no filler or redundant phrasing. Every word contributes to meaning.

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?

For a one-parameter tool with low complexity, the core purpose is conveyed clearly. However, there is no output schema and no annotations, so the description should ideally explain what the tool returns or what state it creates for subsequent sibling tools like list_theorems and get_theorem. This leaves the post-conditions somewhat ambiguous.

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?

The schema only defines a bare 'path' string with 0% description coverage. The description adds that this path should point to a local LaTeX paper, which is essential disambiguation, especially against load_arxiv_paper. It could add constraints like file extension or path type, but the one-parameter case is well served.

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 verb 'load' and a specific resource 'local LaTeX paper', plus the outcome 'build its theorem graph'. The word 'local' distinguishes this from the sibling load_arxiv_paper, so an agent can tell them apart without additional context.

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 word 'local' implies this tool is for local LaTeX files rather than arXiv papers, but the description never explicitly says when to use this tool vs load_arxiv_paper or names the alternative. Usage guidance is thus only implied, not stated.

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

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/lotchuazzz-crypto/papergraph-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server