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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context by showing how the input flags (hasEvents, hasDiff) affect the suggestions, using examples. It also implies that the tool is context-dependent, which is beyond the 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 appropriately concise and well-structured. The first sentence states the purpose, the second gives usage timing, and examples are presented in a clear bullet list. Every sentence contributes information without 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 simple tool with two boolean parameters and no output schema, the description covers purpose, usage timing, and parameter semantics. A minor gap is that it does not explicitly describe the return format (e.g., list of action objects), but the examples and phrase 'present follow-up options' make it sufficiently clear. Overall, it is complete enough for an agent to invoke 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?

The schema description coverage is 100%, giving baseline 3. The description adds semantic value by providing concrete example parameter combinations (e.g., { hasEvents: false, hasDiff: false } for standard post-query, { hasEvents: true, hasDiff: true } for events+difference), which clarifies how the flags map to real investigation flows.

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 tool 'Suggests interesting actions the user can perform next' with specific examples (save a view, set up an alert, share to Slack, drill down, compare periods). It also distinguishes itself from siblings like suggest_groupby and suggest_usage_metrics by focusing on follow-up actions rather than metrics or group-by suggestions.

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 explicit when-to-use guidance: 'Call this after investigation flows (after query or get) to present follow-up options to the user.' It gives concrete usage scenarios with the parameter examples, but does not explicitly mention when not to use it or contrast with alternatives, so it falls short of a 5.

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