get_contacts

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

Annotations declare readOnlyHint=true, and the description adds context that it reads from a local index (auto-refreshed if stale or empty) and reflects the last sync. This explains the data source and freshness behavior beyond the annotation. It also clarifies that results are frequency-derived, not from an address book, adding transparency about data provenance.

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 compact and front-loaded: it states the primary function, then usage, then data source caveats. Every sentence adds value, with no fluff or 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?

Given the tool's simplicity (one optional param), the description covers purpose, usage, behavioral traits (read-only, auto-refresh), and caveats. It lacks explicit return format info, but no output schema exists and the tool is simple enough that this is not critical. It effectively compensates.

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?

The schema has 100% coverage with a single 'limit' parameter that has a default and description ('Maximum contacts to return'). The description does not add extra semantics beyond that, but since the schema is self-explanatory, a baseline 3 is appropriate.

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 what the tool does: returns the most frequently contacted email addresses ranked by interaction volume within the analytics sample window. It distinguishes itself from sibling tools like top_senders and search tools by specifying frequency-derived ranking and usage for identifying key correspondents.

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 says 'Use to identify key correspondents or to pre-populate recipient lists,' which provides clear context for when to use it. However, it does not explicitly state when NOT to use it or alternatives, though the note about not being a Proton contacts address book implicitly warns against using it for address book purposes.

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