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 |
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 overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical router variants, and entity_profile/compare_entities/recent_changes/ai_visibility_check all inspect companies from overlapping angles. The six Polymarket tools form a tightly-overlapping mini-domain that further crowds the surface.
All names are snake_case, but verbs are inconsistently used: many tools are noun phrases (citation_count, entity_profile, polymarket_edges) while others start with verbs (ask_pipeworx, compare_entities, validate_claim). Some prefixes like ask_* and polymarket_* help, but the overall verb/noun pattern is not coherent.
37 tools is well above the typical 3–15 tool scope, and several are redundant variants (three ask_pipeworx modes) or hyper-specific sub-tools (six Polymarket tools). The server name suggests a focused citation service, but only six tools actually address citations, leaving the set bloated with unrelated data query and memory utilities.
For a general data-query gateway, the surface is quite broad and covers lookup, profiling, comparisons, subscriptions, and memory. But as an OpenCitations server it lacks a way to discover papers by topic and the breadth of the other domains is unwieldy and unowned—so notable gaps exist in any plausible stated purpose.