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PaperGraph MCP

PaperGraph MCP

by lotchuazzz-crypto
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

workspace_get_paper

Retrieve metadata and counts for a stored paper by providing its paper ID to access key details and usage statistics.

Instructions

Return metadata and counts for one stored paper.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "paper_id": "<paper_id>"
    },
    "name": "workspace_get_paper"
  }
}

Input Schema

NameRequiredDescriptionDefault
paper_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.1

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It states a read-only return behavior, which is useful, but it does not disclose error/not-found behavior, prerequisites such as an open workspace, or what 'counts' specifically refers to.

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?

One short, front-loaded sentence with no filler. Every word contributes to describing the tool's core functionality.

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 simple one-parameter getter, the description covers the basics, but with no annotations and no output schema, the vague phrase 'metadata and counts' leaves return structure and the meaning of 'counts' to inference.

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?

The schema has only one parameter, paper_id, with 0% description coverage. The description does not explain the format or source of paper_id, but the name plus 'one stored paper' makes the parameter's referent reasonably clear, adding limited semantic context.

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 description uses a specific verb ('Return') and a specific resource ('one stored paper'), and indicates the result content ('metadata and counts'). It clearly differentiates this from list-type siblings, though it does not explicitly name an alternative.

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 phrase 'for one stored paper' implies this tool is for retrieving a single paper's metadata and counts, but the description gives no explicit when-to-use vs. when-not-to-use guidance and does not mention alternatives like workspace_list_papers.

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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