references_count"How many references does paper [DOI] have" / "how big is the bibliography of [paper]" — outgoing reference count for a DOI. Fast version of references when you only need the number.
| Name | Required | Description | Default |
|---|---|---|---|
| doi | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Outgoing reference count for the DOI |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "doi": "10.1371/journal.pone.0123456"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Outgoing reference count for the DOI",
+ "type": "integer"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive, so the bar is lower. The description adds value by revealing it's a 'fast' variant and clarifies the count is 'outgoing,' setting expectations for performance and direction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact sentences with natural-language examples; no filler. The phrase 'outgoing reference count' is a precise summary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema and strong annotations, the description covers purpose, usage guidance, and parameter semantics. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains that the `doi` parameter refers to a paper identifier in context ('paper [DOI]'), and the example in the schema supplements formatting. With 0% schema coverage, this is enough to infer what to pass.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs like 'count' and 'has' to indicate a numeric result, and clearly identifies the resource as a paper's DOI and its outgoing references. It distinguishes from the sibling `references` tool by noting it's the 'fast version' for just the number.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Fast version of `references` when you only need the number,' naming the alternative and the condition. This provides clear guidance on when to use this tool instead of the full reference list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.