citation_graph
Explore citation network: who cites a paper and what it references.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| doi | No | ||
| paper_id | No | ||
| direction | No | citing,cited_by,both |
Explore citation network: who cites a paper and what it references.
| Name | Required | Description | Default |
|---|---|---|---|
| doi | No | ||
| paper_id | No | ||
| direction | No | citing,cited_by,both |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior, but it only states the general function. It does not mention required input parameters (doi vs paper_id), the meaning of direction values, or the response format. No side effects or access requirements are disclosed.
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?
The description is a single, efficient sentence that immediately conveys the tool's purpose. It is well-structured and front-loaded with the key concept, with no unnecessary words or repetition.
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?
Given the tool has 3 parameters and no output schema or annotations, the description is too sparse. It does not explain how to specify a paper (DOI or internal ID), what the response looks like, or the semantics of the direction parameter. The description leaves too much unspecified for successful invocation.
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 only 33% (only 'direction' has a bare list of possible values). The description does not explain the roles of 'doi' or 'paper_id', nor does it clarify how 'direction' relates to the cited/references phrasing. The tool description adds minimal semantic value beyond the schema.
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 identifies the tool as exploring citation networks, specifying both directions ('who cites a paper' and 'what it references'). It distinguishes itself from sibling tools like 'paper_detail' or 'search_papers' by focusing on citation relationships rather than general paper details or search.
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?
No guidance is provided on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or preferred contexts. The description merely implies use for citation exploration, but offers no explicit direction on when to choose it over related tools like 'paper_detail'.
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 target distinct resources (papers, authors, citations, DOIs). arxiv_search and search_papers both search for papers, but they are differentiated by corpus (preprints vs all). compliance_research is a convenience wrapper for compliance topics but is still distinct.
Tool names mix noun-noun (author_papers, citation_graph), noun-verb (arxiv_search, doi_lookup), and verb-noun (search_papers) patterns. While each name is readable, there is no consistent verb_noun convention, making it harder to predict tool names.
At 11 tools, the set is well-scoped for a research discovery platform. Each tool covers a necessary aspect: search, metadata, authors, citations, recommendations, trending, and system health.
The surface covers core research workflows: searching, retrieving details, author exploration, citation analysis, recommendations, and trending. Minor gaps exist (e.g., no journal-specific search or batch export), but agents can accomplish typical tasks without dead ends.