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adamamer20-paper-search-mcp-openai

by ai.smithery
OverviewDiscussionsAdmin

read_iacr_paper

Read and extract text content from an IACR ePrint paper PDF.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paper_idYes
save_pathNo./downloads

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • addedInput schema / $schema
      Added value: +"http://json-schema.org/draft-07/schema#"
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / paper_id / title
      Removed value: -"Paper Id"
    • removedInput schema / properties / save_path / title
      Removed value: -"Save Path"
    • removedInput schema / title
      Removed value: -"read_iacr_paperArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "title": "Result",
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "read_iacr_paperOutput",
-  "type": "object"
-}New value: +null
  2. First observed

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden. It mentions 'extract text content' but fails to clarify the side effects implied by the 'save_path' parameter (whether it saves the PDF, the extracted text, or both), output format, or idempotency.

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?

The single sentence is front-loaded with the action and target, containing no wasted words. However, extreme brevity contributes to under-specification given the lack of supporting schema documentation.

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?

Given zero schema descriptions, no annotations, and ambiguous interaction between text extraction and file saving, the description is insufficient. It omits critical details like paper ID format, return value structure, and file system side effects.

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

Parameters2/5

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

Schema description coverage is 0%, requiring the description to compensate. It fails to explain the 'paper_id' format (e.g., whether it's the full URL, the year/number ID, or an integer) or the purpose of 'save_path' relative to the extraction behavior.

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 uses specific verbs ('Read and extract') and identifies the exact resource ('IACR ePrint paper PDF'), clearly distinguishing it from siblings handling arXiv, bioRxiv, or other sources.

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?

While the description identifies the target source (IACR), it provides no guidance on when to use this tool versus the sibling 'download_iacr' or versus 'read_arxiv_paper' and other read tools. No prerequisites or exclusion criteria are mentioned.

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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