MCP Refchecker
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Only one tool exists, so there is no ambiguity between tools. The single tool has a clear, singular purpose.
Naming Consistency3/5With only one tool, consistency with other tools is not applicable. The name itself (verify_citation) follows a reasonable verb_noun pattern, but no pattern across tools can be evaluated.
Tool Count2/5The server provides only one tool for the domain of citation verification. While verifying a citation is a focused task, real-world usage often requires additional operations like batch verification, retrieving paper details, or checking multiple citations at once, making the single tool feel too limited.
Completeness2/5The tool covers a single operation (verifying a citation) but lacks other related operations such as searching for papers, listing citations for a paper, or bulk verification. For a comprehensive citation checking service, the coverage is incomplete.
Average 4.2/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains what the tool checks (title, authors, year, venue) and the sources used, adding behavioral context beyond the schema. However, with no annotations provided, this dimension carries full weight; the description does not cover all potential behaviors such as rate limits, authentication requirements, or error handling, but given the straightforward nature of a citation verification tool, the disclosure is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear first paragraph stating the tool's purpose followed by a bulleted list of parameters. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (6 parameters, 1 required, output schema present), the description covers the essential information. It explains the verification process and parameter meanings, but lacks details on output structure. However, since an output schema exists, this omission is acceptable. The description is sufficiently complete for effective usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides brief semantic information for each parameter, defining what they represent (e.g., 'DOI of the paper', 'arXiv ID'). However, the input schema's title fields already convey most of this information (e.g., 'Doi', 'Arxiv Id'), and the description does not add significant new meaning. Schema description coverage is 0%, so the description compensates minimally.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: verifying academic citations by checking against three specific databases (Semantic Scholar, OpenAlex, CrossRef). It precisely describes the verification outputs: existence check and mismatch flags for title, authors, year, or venue. This is specific and informative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists parameters with their types and example formats, providing guidance on how to use the tool. However, it does not indicate when not to use this tool or mention alternatives, which would be beneficial since there are no sibling tools. The clarity of the parameter descriptions partly compensates.
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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