Skip to main content
Glama
czwziy

scholar-toolkit-mcp

by czwziy

read_ssrn_paper

Attempts to read an SSRN paper by its ID. The SSRN connector is metadata-only, so this tool returns an error message.

Instructions

Read paper content from SSRN.

Note: SSRN connector is metadata-only and read is not supported.

Args: paper_id: SSRN paper identifier. save_path: Directory where the PDF is/will be saved (unused). Returns: str: Error message from metadata-only SSRN connector.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paper_idYes
save_pathNo./downloads

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description is fully transparent about the tool's behavior: it explicitly states that read is not supported and that the connector is metadata-only, and it specifies the return value is an error message. This exceeds expectations given no annotations are provided.

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

Conciseness3/5

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

The description consists of three sentences plus an Args/Returns block. It is relatively concise, but the first sentence is misleading and could be removed to improve clarity. The structure is standard but not optimized for quick comprehension.

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 that the tool is a stub, the description adequately covers the limitation and return format. However, it fails to mention that other read tools (like read_arxiv_paper) are functional, which would help the agent decide to use alternatives. With many sibling read tools, this omission reduces completeness.

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

Parameters4/5

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

The description adds meaning beyond the input schema for both parameters: 'paper_id: SSRN paper identifier' and 'save_path: Directory where the PDF is/will be saved (unused)'. This is valuable since schema coverage is 0%. The explanation that save_path is unused is a notable clarification.

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

Purpose2/5

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

The description initially states 'Read paper content from SSRN' which suggests it is a functional read operation, but then immediately contradicts by stating 'SSRN connector is metadata-only and read is not supported.' This creates confusion about the actual purpose. A clearer statement like 'Unsupported operation' would be more accurate.

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

Usage Guidelines1/5

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

The description provides no guidance on when to use this tool vs alternatives. Since the tool is non-functional, it should explicitly advise against use and direct to working tools like download_ssrn or search_ssrn. Sibling tools include multiple read_*_paper tools that are presumably functional, but no differentiation is made.

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/czwziy/paper-toolkit-mcp'

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