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HypePaper

by app.hypepaper
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expert_federation

Which topic experts hold the same entity — a paper (by arXiv id), method, model, dataset, benchmark or metric — and under which node id in each. Pass a name or a node id; topic_id narrows the starting expert. Use to move a question to the expert that knows an entity best, or to see how widely a method is used across fields. [Free · 1 credit]

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": {
      "entity": "<entity>"
    },
    "name": "expert_federation"
  }
}

Input Schema

NameRequiredDescriptionDefault
entityYesEntity name (exact, case-insensitive) or node id.
topic_idNoTopic id of an expert (from list_experts).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the cost model (free, 1 credit), the matching behavior (exact, case-insensitive), the accepted input forms (name or node id), and the shape of the answer (experts plus their node ids). It omits what happens when nothing matches and whether results are ranked or capped.

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?

The core question is front-loaded in the first clause, followed by input guidance and intended use, then a short cost tag. It is tight overall, though the parenthetical entity list and the trailing credit note add mild bulk.

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?

For a two-parameter tool with no output schema and no annotations, the description covers inputs, cost, and the general content of the response well enough to call it correctly. Only the no-match behavior and result ordering remain unspecified.

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 100%, so baseline is 3, but the description adds meaning beyond the schema by characterizing topic_id as narrowing the starting expert, implying a traversal rather than a plain filter. It also confirms entity accepts a node id as well as a name, clarifying the dual-purpose parameter.

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 states a precise question the tool answers: which topic experts hold a given entity, and under which node id. It enumerates the supported entity kinds (arXiv paper, method, model, dataset, benchmark, metric), so the resource is unambiguous. It does not name a sibling tool to contrast with, which keeps it below a 5.

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?

"Use to move a question to the expert that knows an entity best, or to see how widely a method is used across fields" gives two concrete situations for calling it. It also explains that topic_id narrows the starting expert, implying a scoping decision. No exclusions or explicit alternatives are given, so it stops short of a 5.

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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