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

Without annotations, the description carries the burden of disclosing behavior. It does so well by explaining the SPECTER-based similarity, the re-ranking behavior with category_id, that results remain under 'related' with proximity tiers, and that the ordering is not an authoritative classification. This adds meaningful context beyond a simple 'get similar papers' phrasing.

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 two sentences, front-loaded with the core purpose in the first sentence and the optional category_id behavior in the second. Every clause earns its place, with no redundant text or filler.

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 tool's moderate complexity (3 params, no output schema, no annotations), the description is quite complete. It covers the core functionality, explains how the optional parameter modifies the behavior, and warns about the non-authoritative nature of the re-ranking. The detailed schema descriptions for parameters fill any remaining gaps about defaults and tiers.

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 100%, so the baseline is 3. The description adds some semantic context for category_id ('semantic lens') but the schema already thoroughly documents each parameter, including the effect of category_id and limit defaults. Therefore, the description provides marginal added value 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: 'Get papers similar to a given paper (recommendations based on SPECTER embeddings).' This uses a specific verb ('get') and a specific resource (related papers), and distinguishes it from citation-based sibling tools like get_citations and get_references by explicitly mentioning SPECTER embeddings.

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 clear context for when to use the tool (for similar-paper recommendations) and explains the conditional usage of category_id to re-rank results. However, it does not explicitly exclude alternatives or mention when not to use it versus sibling tools, stopping short of a 5.

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