Retrieve cumulative token savings and cost avoided across all tool calls to gauge modeled session efficiency and quantify reduced data-retrieval usage.
Return cumulative token savings and cost avoided across all tool calls. Savings are modelled estimates, not per-call measurements.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.31.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation readOnlyHint=true already establishes safety. The description adds valuable behavioral context beyond that by warning that savings are modelled estimates and not precise per-call measurements, which prevents an agent from overstating the confidence in results.
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 tight sentences. The first front-loads the action and result; the second adds an essential caveat. No words are wasted.
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 zero parameters and no output schema, the description covers what is returned and its limitations. It could have mentioned the units or exact return shape, but for a simple no-arg stat tool this is sufficiently complete.
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?
Input schema is empty, so parameter documentation is a non-issue. The description still clarifies scope with 'across all tool calls,' which gives all the semantic context needed for a zero-parameter call.
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 states a specific verb and resource: 'Return cumulative token savings and cost avoided across all tool calls.' It is immediately clear what the tool produces and how it differs from a per-call measurements tool, thanks to the second sentence explicitly marking these as estimates rather than per-call readings.
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?
It tells you the tool returns aggregate session-level savings, but gives no guidance on when to use this over any sibling tool. No alternative tools are named, and no exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.