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graph_topic

Search any research topic to generate an interactive citation graph. Papers are shown as nodes scaled by citation count and colored by year, with edges revealing keyword, venue, and similarity connections.

Instructions

Search a topic and render an interactive citation/relatedness graph as a self-contained HTML file.

Nodes are papers (size scales with citation count, color by year); edges connect papers that share keywords or a venue, plus similarity links radiating from the top result. Returns the local HTML path. Open it in a browser to explore or screenshot the landscape.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
limit_per_sourceNo
related_limitNo
from_yearNo
to_yearNo
open_access_onlyNo
Behavior3/5

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

No annotations are provided, so the description must bear full behavioral burden. It describes node encoding (size, color) and edge logic, but omits details about failure modes (e.g., empty results), authentication, or rate limits. The behavior is mostly transparent but incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the core action, and every sentence provides unique information. No redundancy or unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a graph-generation tool and lack of output schema, the description explains the return value (HTML path) and visual encoding. However, it misses parameter explanations and does not set expectations about performance or source dependencies, leaving gaps for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 6 parameters, the description must compensate but does not. Only 'topic' is implied. No explanation is given for limit_per_source, related_limit, from_year, to_year, or open_access_only, leaving the agent without necessary guidance for parameter usage.

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 purpose: searching a topic and rendering an interactive citation/relatedness graph as an HTML file. The verb 'search' and 'render' are specific, and the resource (citation graph) is distinct from siblings like search_literature or deep_read_topic.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for visual exploration of citation relationships but does not explicitly state when to use this tool over alternatives or provide usage exclusions. No mention of when-not to use or comparison with sibling tools.

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

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