get_backup_status

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

Annotations already declare readOnlyHint=true, so the description adds value by detailing the output: backup status, age, integrity check, color-coded freshness, heartbeat score, call volume, cadence. No contradictions, and it enhances transparency of what the tool returns.

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?

Concise yet informative: first sentence summarizes the tool, followed by elaboration and clear usage guidance. No wasted words, well-structured.

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?

No output schema, but the description lists the key metrics returned (backup status, age, integrity check, data freshness colors, heartbeat score, call volume, cadence). This is sufficient for an agent to understand the tool's output, though minor details like format or frequency could be added.

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?

There are no parameters, so the description naturally adds no parameter info. Baseline for 0 parameters is 4, and the description does not need to compensate. Schema coverage is 100% (no params).

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 returns platform health metrics including backup status, data freshness, heartbeat score, etc. It distinguishes from sibling tools like get_changes by specifying it is for platform/infra health, not specific dataset freshness.

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?

Explicitly states when to use (for trust/uptime signals before production reliance) and when not to use (for specific dataset freshness, recommending get_changes instead). Provides clear context and alternatives.

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