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rag-reference-discovery-mcp

discover_references

Discover and rank scholarly references from research text using Crossref, OpenAlex, and DataCite, with optional Zotero validation for verified candidate lists.

Instructions

Discover and rank public scholarly metadata without claiming validation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations at all, the description carries the full burden. It does disclose a meaningful behavioral trait: the tool does not validate metadata and merely ranks public scholarly output. However, it says nothing about return format, data sources, limitations, or side effects, leaving significant behavioral context undisclosed.

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 compact sentence that front-loads the core purpose and adds the validation caveat. Every word earns its place; there is no fluff or repetition.

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

Completeness2/5

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

Despite the rich schema, this is a 14-parameter nested request tool with no annotations and no output schema. The one-sentence description covers only the high-level intent and lacks guidance on how to structure requests, interpret results, or choose validation-related options, so it is not fully adequate for correct invocation.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no information about the nested request object or any of its 14 properties such as queries, validation_mode, max_results, or publication year filters. The agent is left to infer all parameter semantics from the raw JSON schema alone.

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 uses a specific verb ('Discover and rank') and a specific resource ('public scholarly metadata'), and the caveat 'without claiming validation' clearly differentiates it from sibling validate_reference and discover_and_validate_references. An agent can tell this is a discovery-only tool even before examining the schema.

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 'without claiming validation' implies this tool is for unvalidated discovery, but there is no explicit when-to-use or when-not-to-use guidance, nor is any sibling alternative named. Usage context is implied rather than stated.

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