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Glama

Opencitations

by io.github.pipeworx-io

Citations

citations
Read-onlyIdempotent

"Who cites paper [DOI]" / "what papers reference [DOI]" / "incoming citations to [paper]" / "what work has cited [study]" — DOIs that CITE the given DOI (reverse-direction from references). Use for impact analysis, follow-on research discovery, "is this paper influential" questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doiYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
citationsNoDOIs that cite the given DOI

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "doi": "10.1371/journal.pone.0123456"
+  },
+  {
+    "doi": "10.1016/j.cell.2020.01.001"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "citations": {
+      "description": "DOIs that cite the given DOI",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior. The description adds valuable context that it's the reverse direction from references, clarifying the semantic direction of the operation. However, it doesn't mention potential output format or edge cases (e.g., no citations found), but the output schema likely covers return structure.

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 description is compact but rich, using multiple example phrasings to convey the same concept. It's slightly longer than minimal but every part adds value, including the usage guidance. The front-loaded examples make the purpose immediately clear.

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?

For a single-parameter tool with an output schema, the description covers purpose, usage, and direction. It fully explains what the tool does and when to use it, making it complete within its context.

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?

The input schema only specifies 'doi' as a string without further description (0% coverage). The description compensates by repeatedly using 'DOI' in examples and clarifying that the tool operates on a given DOI. This makes the parameter's meaning clear, though it doesn't explicitly state it's a single string parameter.

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 clearly states the tool's function: it returns DOIs that cite a given DOI (incoming citations). It uses explicit verbs like 'cites' and 'reference' and provides example queries. It distinguishes itself from the sibling 'references' tool by noting it's the reverse direction.

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?

The description gives explicit usage scenarios: 'Use for impact analysis, follow-on research discovery, "is this paper influential" questions.' It also contrasts with references, making it clear when to use this tool vs. the alternative.

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

All Opencitations toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are described as currently identical, and citation vs citations differ only by pluralization while actually accepting different ID types (OCI vs DOI). The server is named Opencitations but 31 of 37 tools serve unrelated purposes, so an agent cannot infer what the set is for without reading very long descriptions.

Naming Consistency3/5

All names are snake_case and family prefixes (polymarket_*, ask_pipeworx_*, pipeworx_*) give some predictability. However, conventions are mixed: bare resource nouns (citation, citations, references, metadata) coexist with verb_noun tools (resolve_entity, validate_claim) and noun phrases (recent_changes, entity_profile, deep_research), so there is no single pattern that lets an agent predict tool names.

Tool Count2/5

37 tools is well past the 25+ threshold for a heavy set, and most are redundant with the server's own router tools — ask_pipeworx already reaches 5,759 underlying tools, making many direct tools overlapping conveniences. The scope also wildly overshoots the server name: only 6 of 37 tools serve the Opencitations citation-graph domain.

Completeness3/5

For the named OpenCitations domain, the core citation-graph read operations exist (metadata, incoming citations, outgoing references, counts, OCI record lookup), but there is no paper/DOI discovery or search tool — an agent must already possess a DOI, a dead end for title/author queries. The broader accidental domain (data routing, company research, prediction markets, monitoring) is covered unusually well, but that does not serve the server's stated purpose.

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