tokmeter_providers

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 covered. The description usefully discloses what each row reports (cost, tokens, model count, share), but is silent on default scope behavior, empty results, or ordering — modest added value beyond structured fields.

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 with the core comparison stated first and return fields second. No filler; every sentence carries information, though the final sentence is somewhat redundant with the second.

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 steps in to describe the returned per-provider metrics, which is the right coverage decision. Only a note on the default scope ('all') and aggregation behavior is missing for full completeness.

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%, with the scope enum and provider filter fully documented in the schema itself. The description adds no parameter-level detail (e.g. default scope, how project substring matching works), so the baseline 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?

The description uses a specific verb ('Compare') and resource ('token usage across providers'), names example providers, and enumerates the output metrics (cost, tokens, model count, share). It is clear what the tool does, though it never explicitly contrasts itself with near-siblings like tokmeter_leaderboard or tokmeter_compare.

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 closing sentence gives an implied use case ('understand which AI coding agents are most used and costly') but offers no when-not guidance and does not name an alternative among the many tokmeter_* siblings. An agent must infer selection from the purpose alone.

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