Trending papers by curve-model hype or spotlight for a window, with momentum and rank change. [Free · 1 credit]
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "trending_papers"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | hype | |
| limit | No | ||
| window | No | week |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full load. It does disclose the returned content ('momentum and rank change') and the cost ('Free · 1 credit'), which are genuinely useful, but says nothing about read-only nature, authentication, rate limits or response size beyond the schema's limit cap.
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?
A single front-loaded sentence plus a short cost tag; nothing is padded. The cost bracket is separated cleanly from the semantic content.
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 three-parameter, enum-driven list tool with no annotations and no output schema, the description conveys purpose, return fields, and pricing adequately, but the domain terms and the limit parameter remain unexplained.
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 description coverage is 0%, so the description must compensate. It does explain sort's two modes and names 'window' explicitly, but leaves the 'limit' parameter completely unaddressed and does not define what 'hype' or 'spotlight' actually measure.
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?
States a specific resource (trending papers) plus the two ranking modes drawn from the sort enum and a time window, which is enough to separate it from static-list siblings like sota_papers or conference_papers. The jargon 'curve-model hype' and 'spotlight' is only partly self-explanatory, which keeps it below a 5.
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 never says when to choose trending_papers over the many adjacent discovery tools (sota_papers, similar_papers, entity_trends) or when it is inappropriate. Use for trend discovery is only inferred from the word 'trending'.
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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