get_stale_relationships

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

No annotations are provided, so the description carries the behavioral disclosure burden. It clearly explains the two selection criteria (no-contact days, importance level) and the use case. It doesn't specify return format details, but given that an output schema exists, the description reasonably focuses on the filtering logic and intent. The behavioral characteristics (read operation, staleness heuristic) are well disclosed.

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 with the primary purpose in the first sentence. The follow-up content is structured with a bullet-style list and a use-case sentence. Every sentence earns its place: purpose, criteria, and when-to-use. No 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?

With 3 optional parameters, 100% schema coverage, an output schema, and no nested objects, this is a moderately simple tool. The description captures the selection logic and use case thoroughly. The only minor gap is not specifying how results are ordered (e.g., by staleness severity or importance), which could affect agent expectations, but overall the tool is well-covered.

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 schema already fully documents all three parameters (limit, days_threshold, min_importance) with defaults and explanations. The description adds value by naming the actual filtering concepts (no contact in N days, importance level) that map to the parameters, but this is modest added value over the already-complete schema. Baseline 3 is appropriate since the schema does the heavy lifting.

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 verb+resource ('Get important people you haven't contacted recently') and distinguishes itself from sibling tools by focusing on relationship staleness and importance. It explicitly enumerates the filtering criteria (no-contact days, importance level), making the purpose unmistakable and distinct from follow-up, commitment, delegation, and meeting tools.

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 this tool ('to identify clients, partners, or colleagues you should reach out to') and explains the selection criteria. It doesn't explicitly name alternatives or exclusion cases, but given the large sibling set, the 'important people you haven't contacted' framing provides sufficient differentiation guidance without needing to list every sibling.

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