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MAD Synapse · Web & Research

Citation / DOI lookup

doi_lookup
Read-onlyIdempotent

Resolve a DOI — or search a paper title — to full citation metadata: title, authors, journal, year, citations count, publisher, license, and a ready-made APA/BibTeX citation. Crossref's open metadata (150M+ works). Search mode returns the top matches for a title/author query. When to use: For citation metadata of a known paper; to search preprints by topic use arxiv_search. Price: $0.001 per call (10 free/day; after that a payment-required result lists x402 options). Errors: returns isError with a message for invalid input or an upstream failure (not charged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doiNoe.g. 10.1038/nature14539
limitNoHow many matches to return when searching by title. Range 1-20. Default 5.
queryNotitle/author search instead of a DOI

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
apaNo
doiNo
urlNo
typeNo
yearNo
foundNo
issueNo
pagesNo
titleNo
bibtexNo
volumeNo
authorsNo
journalNo
licenseNo
cited_byNo
publisherNo
referencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations cover safety (readOnly/idempotent/non-destructive), but the description adds materially more: upstream source (Crossref, 150M+ works), pricing and free-tier quota ($0.001/call, 10 free/day, x402 payment-required result), and error semantics (isError on invalid input or upstream failure, not charged). These are exactly the operational traits annotations cannot express.

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?

Front-loaded with the core action and return fields, then labeled 'When to use / Price / Errors' sections. Dense and information-rich with very little waste, though the field enumeration plus three trailing clauses make it longer than strictly necessary.

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

Completeness5/5

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

An output schema exists so return values need not be documented, yet the description still previews them; combined with mode selection, billing, and failure behavior, nothing an agent needs to call this correctly is missing.

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 description coverage is 100%, so the baseline is 3. The description adds real semantic value beyond the schema by framing doi and query as two mutually exclusive entry modes and by stating that search mode returns 'the top matches', which contextualizes the limit parameter's purpose.

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?

Specific verb+resource: 'Resolve a DOI — or search a paper title — to full citation metadata', followed by an enumeration of the exact fields returned. It also explicitly carves itself apart from the nearest sibling ('to search preprints by topic use arxiv_search'), so an agent can route without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Contains an explicit 'When to use' clause plus a named alternative and the condition selecting it (known paper vs. topic discovery via arxiv_search). Both operating modes (DOI resolve vs. title/author search) are stated with their triggers.

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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