tokmeter_cost_optimization_tips

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is known. The description usefully discloses that results are data-derived rather than static and that each tip carries category, severity, and estimated savings, but says nothing about volume of tips, cost, or how to act on them.

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?

Two sentences, front-loaded with the action, no filler. Minor redundancy between 'cost optimization recommendations' and the following 'tips' sentence, but nothing that should be cut.

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 no output schema, the description helpfully sketches the return shape (category, severity, estimated savings), which is what an agent needs to consume it. The remaining gap is behavior when the optional period is omitted, which is left unstated.

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 single optional 'period' parameter is fully documented in the schema, including its enum values, and the description adds nothing further about it (no default when omitted). With 100% schema coverage the baseline of 3 applies.

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?

States a specific verb and resource: analyze usage patterns and generate cost optimization tips, with the concrete dimensions covered (cache efficiency, model selection, conversation length, spending distribution). It does not differentiate itself from strongly overlapping siblings such as tokmeter_cache_efficiency, tokmeter_model_advisor, and tokmeter_efficiency, which an agent would need to tell apart.

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?

Usage is only implied — 'based on actual data' signals this reads real usage rather than offering generic advice. There is no explicit when-to-use, no stated prerequisites (e.g., whether a minimum amount of history is needed), and no routing to or from the overlapping sibling tools.

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