get_paper_citationsList papers that CITE a given paper (the works citing it), with their titles, authors, year, and citation counts. Useful for forward citation tracing and finding follow-up work. Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max citing papers to return (default 10, max 25). | |
| paper_id | Yes | Paper identifier. A Semantic Scholar ID, or prefixed: "DOI:10...", "arXiv:2106.15928", "CorpusId:...". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "limit": 15,
+ "paper_id": "CorpusId:215416146"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds the 'Keyless' behavioral detail and mentions output fields, but does not explain pagination, error handling, or rate limits. The added value is moderate.
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?
Three sentences: first states purpose and output, second gives usage context, third adds a key feature. No redundant information, front-loaded with core function. Every sentence earns its place.
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?
The description explains output fields and usage, but lacks details on ordering (e.g., by citation count?), default limit, and behavior when paper_id is invalid or has no citations. For a simple listing tool with good annotations, it is adequate but could be more complete.
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?
Schema coverage is 100%: both 'limit' and 'paper_id' are described with types, defaults, and examples. The description does not add further parameter semantics; it only mentions output fields. With high schema coverage, baseline score of 3 is appropriate.
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 clearly states the tool lists papers that cite a given paper, specifying output fields (titles, authors, year, citation counts). This specific verb+resource distinguishes it from siblings like 'get_paper' (retrieves a single paper's details) and 'search_papers' (search by query).
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?
The description says 'Useful for forward citation tracing and finding follow-up work,' clearly indicating when to use it. It also notes 'Keyless,' implying no authentication required. However, it does not explicitly mention when not to use it or suggest alternative tools (e.g., for reverse citations).
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.
Most tools have clearly distinct purposes, especially the core ones like get_paper, search_papers, and entity_profile. However, some pairs like ask_pipeworx and ask_pipeworx_grounded, or the polymarket tools, could cause momentary confusion, though descriptions help differentiate.
Naming patterns are inconsistent: tools use verb_noun (e.g., get_paper), noun_phrase (e.g., polymarket_arbitrage), and bare verbs (e.g., forget, recall). There is no unifying pattern, and styles like 'pipeworx_feedback' vs 'search_papers' further add to the inconsistency.
With 34 tools, the set covers a broad range of domains (academic papers, company data, prediction markets, memory, subscriptions). While the scope justifies the number, it feels slightly heavy and could benefit from consolidation or clearer grouping.
The tool set covers major functionalities for research, data retrieval, and monitoring, with only minor gaps (e.g., limited to US public companies, npm-only dependency scanning). Overall, the surface is comprehensive for the stated capabilities.