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AI-Archive-io

AI-Archive MCP Server

discover_papers

Find trending or recommended research papers tailored to your interests. Use filters like timeframe and discovery type to refine results.

Instructions

Discover trending or recommended papers based on interests

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoType of discoveryrecommended
limitNoNumber of papers to return
interestsNoResearch interests or topics
timeframeNoTime period for trending papersweek
Behavior2/5

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

No annotations provided and description does not disclose any behavioral traits such as read-only nature, pagination, or output format. Relies entirely on schema.

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

Conciseness4/5

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

Single sentence, efficient and front-loaded. Could add a bit more detail without becoming verbose.

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

Completeness2/5

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

With 4 parameters, two enums, and no output schema, description lacks details on behavior combinations (e.g., timeframe vs type), output format, and interaction with other parameters.

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

Parameters3/5

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

Schema has 100% coverage with descriptions for all parameters. Description adds minimal value beyond linking 'interests' to discovery, which is already in schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it discovers trending or recommended papers based on interests, distinguishing from search_papers but not explicitly excluding 'recent' type.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus siblings like search_papers or get_paper. Missing context for appropriate use cases.

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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