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

Beyond the annotations, the description discloses important behavioral details: fuzzy matching can return many results for common names, results are cached for 24 hours, and the data source is EPO OPS + USPTO. It also tells the agent what to do if the response does not serve the user's need. These are substantive, non-obvious traits that annotations do not provide.

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 front-loaded with purpose and usage, then covers parameters, alternatives, source/cache details, and the feedback path. It is longer than strictly necessary because it repeats annotation flags like 'Read-only', 'No side effects', and 'Idempotent', but the structure is logical and every substantive section 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?

For a two-parameter, read-only tool with a provided output schema and strong annotations, the description is complete. It covers input semantics, fuzzy-match behavior, source and caching, when to choose an alternative, and a fallback feedback procedure. No critical calling context is missing.

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 the schema already documents both parameters well; the baseline is therefore 3. The description adds useful examples ('Smith or John Smith', 'Apple Inc.') and a fuzzy-match warning for inventor_name, which goes slightly beyond the schema without being redundant or excessive.

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 uses a specific verb ('Fetch') and a clear resource ('patent portfolio for a named inventor') with an optional assignee filter. It is immediately distinguishable from patent-retrieval siblings by anchoring on inventor rather than topic or patent number. The fuzzy-match caveat also clarifies what kind of result set to expect.

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?

It explicitly states when to use the tool ('when researching an inventor's work or a company's patent portfolio') and names the key alternative for topic-based needs: legal_search_patents_by_keyword. This gives an agent a concrete decision rule rather than leaving the choice to inference.

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