parse_research_paper

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

With no annotations, the description carries the full burden. It discloses use of Meta's Nougat model and conversion of visual structures, but lacks details on error handling, performance, or file size limits. The Returns section provides some clarity.

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?

The description is well-structured: a clear purpose sentence followed by argument and return descriptions. It is appropriately sized but could be slightly more concise by removing redundant phrasing.

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?

Given the presence of an output schema (not shown but noted), the description adequately covers input parameters and return format. It does not discuss errors or edge cases, but is generally complete for a straightforward parsing tool.

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 coverage is 0%, so the description must explain parameters. It clearly describes 'file_path' as absolute path and elaborates on 'output_format' enum values: 'default', 'mmd', and 'md' with their behaviors. This adds meaningful context beyond the schema.

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?

The description clearly states the tool's purpose: high-accuracy OCR for academic papers and scientific PDFs, converting visual structures to Markdown. It distinguishes itself from the sibling tool 'get_output_settings' by being a parsing tool rather than a settings retrieval tool.

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 provides guidance on when to use each output format option and mentions the 'default' utilizes settings.json. However, it does not specify prerequisites (e.g., file existence) or when to avoid using this tool.

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