get_health_status

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

The description adds substantial behavioral detail beyond the sparse annotations: each observation has its own age/source, current sleep_state is a classification rather than a historical session, cached uses local data, remote reads reconnect, and the tool does not start measurements or change settings. This is strong disclosure of behavior and side effects.

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-loads the high-level resource before adding technical detail. It wastes few words)Skip, though the first sentence is a noun fragment and some concepts are packed densely.

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 output schema covers return values, the description provides most needed operational context: freshness modes, age caps, timeout ranges, and side-effect absence. The main gaps are the unexplained prefer_fresh/require_fresh semantics and lack of explicit sibling routing, but overall an agent can still call this 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 description coverage is 0%, so the description must compensate. It adds useful semantics for max_age_seconds (1..86400, device-state age capped at 120s) and timeout_seconds (10..90), and explains the cached freshness value. However, prefer_fresh and require_fresh are left unexplained, leaving a meaningful gap for a central parameter.

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 enumerates the data categories returned (HR, steps, sleep/workout history, wearing, sleep/activity state), so an agent knows what resource this tool exposes. However, it lacks an explicit verb and does not name sibling tools like get_current_state or query_health, leaving differentiation to inference.

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 provides useful context: cached means local data, remote reads reconnect automatically, and this tool does not start a new measurement. This implicitly steers users needing a new measurement to measure_heart_rate, but it never explicitly states when to use get_health_status instead of get_current_state, query_health, or get_daily_report.

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