Skip to main content
Glama

search_papers

:

Instructions

Fuzzy search references by title in the EndNote library. Use when the user only knows part of the title or keywords, or wants to find related topics. Parameter: query (string, case-insensitive, supports Chinese/English). Returns a list of dicts with fields: id, title, author, year, journal, abstract, keywords, filepath. Typical: search_papers('distillation').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, description carries full disclosure burden. It effectively documents search behavior ('fuzzy', 'case-insensitive', 'supports Chinese/English') and return structure (list of dicts with specific fields). Minor gap: does not explicitly declare read-only status or error behavior, though 'search' implies non-destructive operation.

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?

Four sentences, zero waste: (1) purpose, (2) usage context, (3) parameter semantics, (4) return format + example. Front-loaded with action verb. Every sentence adds value beyond structured schema data.

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

Completeness5/5

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

For a single-parameter search tool, description is comprehensive: covers purpose, selection criteria, parameter details, return schema (complementing the existing output schema), and typical invocation pattern. No critical gaps remain.

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

Parameters5/5

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

Schema has 0% description coverage for the 'query' parameter. Description fully compensates by specifying type (string), case sensitivity (case-insensitive), language support (Chinese/English), and provides a concrete usage example ('distillation').

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?

Description opens with specific verb ('Fuzzy search'), resource ('references'), and scope ('EndNote library'). Clearly distinguishes from siblings list_papers (likely enumeration) and read_paper (likely retrieval by ID) via the 'fuzzy' qualifier and 'search' semantics.

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

Usage Guidelines4/5

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

Explicitly states when to use: 'when the user only knows part of the title or keywords, or wants to find related topics.' Provides clear selection context, though it does not explicitly name alternatives or exclusion criteria (e.g., 'do not use for exact ID lookups').

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DOGGY-SAINT/ENL-Reader-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server