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

No annotations are provided, but the description discloses key behavioral traits: source priority (Elsevier first), fallback order (Springer OA, Europe PMC, arXiv PDF, generic PDF URLs), and the condition that text must be recoverable. It does not mention error handling or empty results, but this is still substantial disclosure beyond the basic purpose.

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?

Three concise sentences, front-loaded with the main purpose, followed by usage and engine specifics. No wasted words; every sentence earns its place.

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 an output schema exists to define return values, the description covers the main usage and engine options. It does not address mutual exclusivity of DOI vs author_name or behavior when neither is provided, but for a 5-param optional tool, it is reasonably complete and well-contextualized.

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 compensate. It explains the DOI-or-author-combo and the engines parameter with allowed values. However, candidate_index and paper_index are not individually explained beyond being part of the combination, leaving ambiguity about their meaning and allowed range.

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 reads full paper text when machine-readable content is recoverable, and explicitly distinguishes it from siblings like scholarfetch_abstract by specifying input combinations (DOI or author+indices) and engine fallback order. The verb 'read' plus resource 'full paper text' is specific and unambiguous.

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?

Provides explicit usage scenarios: use with a DOI or author_name + candidate_index + paper_index, and clarifies the engines parameter syntax with a valid subset. It gives clear context for when to use (when machine-readable content is recoverable) but does not explicitly state when not to use or name alternative tools.

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