tokmeter_model_advisor

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: the output contains actual-vs-alternative cost comparison, a per-model spending breakdown, savings estimates, and a reference pricing table. It omits caveats such as whether savings estimates are heuristic or whether pricing data may be stale, so not a 5.

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?

Three short sentences, front-loaded with the core comparison, then the output shape, then the pricing table. No filler and nothing repeated from the schema or annotations.

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?

There is no output schema, so the description must convey return content, and it does: per-model spend, savings estimates, and a pricing table. It leaves unclear what form the savings estimate takes (per model, aggregate, or ranked) and whether a period default exists, which keeps it from a 5.

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% and both parameters (period enum, project substring) are documented in the schema itself. The description adds no parameter-level meaning, such as the default period or how project matching affects the comparison. Baseline 3 applies when the schema carries the load.

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 concrete verb and resource: compares actual spend against cheaper-model costs, reports per-model spending, and estimates downgrade savings. The scope ('savings if you downgraded expensive models') is specific enough to separate it from a plain model listing like tokmeter_models. It stops short of naming a sibling to differentiate against, so 4 rather than 5.

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 scenario is implied by phrases like 'estimates savings if you downgraded expensive models' and the Opus → Sonnet / GPT-5 → GPT-4o examples. There is no explicit when-to-use vs. when-not-to-use, and no mention of adjacent siblings such as tokmeter_models or tokmeter_cost_optimization_tips that could be confused with it.

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