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llm_savings

Compare actual AI spend to Sonnet baseline across time periods. View savings and efficiency multiplier for today, week, month, and all-time to understand routing value.

Instructions

Show time-bucketed savings dashboard: today / this week / this month / all-time.

Displays actual spend vs Sonnet baseline and the efficiency multiplier (Nx)
for each period. Use this to understand the real dollar value routing provides.

Returns:
    Formatted savings table with efficiency multiplier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the burden of disclosing behavioral traits. It states the tool 'Shows' and 'Displays', implying a read-only operation, but it does not explicitly confirm non-destructive behavior, auth requirements, or side effects. The return type is mentioned, but additional context about data freshness or limits would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: four sentences, no fluff. The key purpose is front-loaded in the first sentence, and each subsequent sentence adds value. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters and an output schema exists (per context), the description covers the purpose, time-buckets, output content, and usage intent. It is fully adequate for an agent to understand what the tool does and what it returns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema coverage is 100% (trivially). The description adds no parameter information, but with no parameters to document, baseline 4 is appropriate. There is no missing meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it shows a time-bucketed savings dashboard, specifying the verb 'Show' and the resource 'savings dashboard'. While it does not explicitly differentiate from siblings like 'llm_dashboard' or 'llm_budget', the focus on Sonnet baseline and efficiency multiplier is distinct enough for an agent to understand its purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'Use this to understand the real dollar value routing provides' which implies a context, but it does not specify when not to use it or mention alternative tools for similar purposes. No exclusions or comparisons to siblings are given, so guidance is implied but not explicit.

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

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