Error Tracking

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

Annotations already establish read-only, idempotent, non-destructive behavior, lowering the burden on the description. The description adds useful operational context beyond annotations: the three distinct response perspectives (summaries, stack-trace instances, and trends) and the dependency between type and errorMessage. It does not contradict annotations.

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 efficient: one lead sentence plus a numbered workflow. Every phrase earns its place, and the most important operational information is front-loaded. 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 12-parameter schema with 100% description coverage and annotations covering safety, the description fills the main remaining gap: the recommended call sequence and the errorMessage dependency. Without an output schema, a bit more about expected return shape would help, but the combination of workflow and rich schema descriptions is largely sufficient.

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 baseline is 3. The description does reinforce the relationship between 'type' and 'errorMessage', but this information already appears in the schema's parameter descriptions. It adds no genuinely new parameter semantics beyond what the schema provides.

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?

Description states a specific verb and resource ('Get error tracking data') and immediately clarifies the three modes (names, events, timeseries), giving an agent a concrete idea of what the tool returns. It does not explicitly compare itself to sibling tools like rybbit_get_event_timeseries or rybbit_get_metric, but the 'error tracking' scope and workflow distinguish it well enough.

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 workflow gives clear in-tool guidance: call type='names' first to discover error messages, then use events or timeseries with an errorMessage. This explicitly teaches the proper sequence and prerequisites. It does not discuss when to prefer alternative sibling tools, but it provides strong usage context within the tool itself.

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