summarize_paper

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that summaries are LLM-generated and specifies the output format for each mode, which is useful. However, it does not mention read-only status, side effects, required permissions, or any potential costs or delays. This is a moderate level of transparency.

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 exceptionally concise and well-structured. It opens with a clear purpose sentence, then lists each mode with its output specification using a bullet-like format. Every sentence contributes value with no redundancy.

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?

The tool appears simple (3 params, 1 required), and the description explains the output for each mode. However, the required parameter 'input_str' is not defined, and the 'model' parameter is left unexplained. No mention of error handling or typical usage scenarios. The description is adequate for a simple tool but has noticeable gaps.

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 description coverage is 0%, so the description must compensate. It does explain the 'mode' enum values thoroughly, adding meaning beyond the schema. However, it does not clarify 'input_str' (presumably the paper text) or 'model' (which model to use). This partial compensation earns a middle score.

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 with a specific verb ('Generate') and resource ('a paper'), and defines three distinct modes of output. This distinguishes it from sibling tools like extract_methods or fetch_paper_text, which have different functions. The mode definitions add precision.

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 explains the three mode options in detail, which helps an agent decide which mode to use. However, it does not explicitly state when to use this tool versus alternatives such as extract_methods or methods_repro_review. The usage context is implied by the name and purpose, but not explicitly guided.

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