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

The description discloses important behavioral traits beyond the readOnlyHint annotation: natural language queries are decomposed via AI into structured filters, date range defaults to last 7 days with a 12-month max lookback, results are returned newest first with a max of 50. These details inform the agent about constraints and default behavior, complementing the annotation.

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 information-dense and well-structured: it opens with the core purpose, then usage context, exclusions, behavioral details, and examples. Every sentence adds practical value without redundancy 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?

For a complex tool relying on AI decomposition and date filtering, the description covers usage conditions, defaults, limits, sorting, and fallback to getPaperDetails. Since there is no output schema, this is sufficient for an agent to select and invoke the tool correctly.

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 100%, so all parameters are already described. The description adds value by providing concrete examples for the query parameter and clarifying date defaults and the AI decomposition mechanism, which enriches understanding but does not fundamentally alter the schema's meaning.

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 that the tool searches quantum computing papers on arXiv, using a specific verb ('Search') and resource ('quantum computing research papers'). It also explicitly distinguishes from siblings by saying 'NOT for jobs (use searchJobs) or researcher profiles (use searchCollaborators)', making it unambiguous when to choose this 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 says 'Use when the user asks about recent research, specific papers, or academic topics in quantum computing' and provides exclusions with explicit alternatives (searchJobs, searchCollaborators). It also mentions using getPaperDetails for full abstract and analysis, giving clear when-to-use and when-not-to-use guidance.

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