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volt_get_savings

Compare actual compute spending against optimal routing to identify savings achieved and missed opportunities across AI inference providers.

Instructions

Compare actual spend against optimal routing. Shows savings achieved and savings missed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
time_rangeNoTime range for the report: today, 7d (7 days), or 30d (30 days)7d

Implementation Reference

  • The handleGetSavings function executes the logic for 'volt_get_savings', retrieving the savings report from the tracker and formatting it.
    export function handleGetSavings(input: GetSavingsInput, tracker: SpendTracker) {
      const report = tracker.getSavingsReport(input.time_range);
    
      if (report.actualSpend === 0) {
        return {
          content: [
            {
              type: 'text' as const,
              text: `No spend data for ${input.time_range}. Record inference calls to see savings opportunities.`,
            },
          ],
        };
      }
    
      return {
        content: [
          {
            type: 'text' as const,
            text: formatSavingsReport(report),
          },
        ],
      };
    }
  • The getSavingsSchema defines the input validation for 'volt_get_savings', specifically the 'time_range' parameter.
    export const getSavingsSchema = z.object({
      time_range: z
        .enum(['today', '7d', '30d'])
        .default('7d')
        .describe('Time range for the report: today, 7d (7 days), or 30d (30 days)'),
    });
  • The formatSavingsReport function is a helper used to construct the text-based savings report output.
    function formatSavingsReport(r: SavingsReport): string {
      const lines: string[] = [
        `Savings Report (${r.timeRange})`,
        '─'.repeat(60),
        `Actual spend:    $${r.actualSpend.toFixed(2)}`,
        `Optimal spend:   $${r.optimalSpend.toFixed(2)}`,
        `Potential savings: ${r.savingsPercent}%`,
        '',
        `Savings achieved (followed recommendations): $${r.savingsAchieved.toFixed(2)}`,
        `Savings missed (ignored recommendations):    $${r.savingsMissed.toFixed(2)}`,
      ];
    
      if (r.savingsMissed > 0) {
        lines.push(
          '',
          `You could save $${r.savingsMissed.toFixed(2)} by following Volt routing recommendations.`,
        );
      } else if (r.savingsPercent === 0) {
        lines.push('', 'You are already using the most cost-effective providers.');
      }
    
      return lines.join('\n');
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'shows' savings, implying a read-only operation, but doesn't clarify if it requires specific permissions, has rate limits, or what the output format looks like (e.g., detailed report vs summary). For a tool with no annotations, this is a significant gap, as it lacks details on behavioral traits like data freshness or computational cost.

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 and front-loaded: two sentences that directly state the tool's purpose and output. There is zero waste—every word contributes to understanding what the tool does. This efficient structure makes it easy for an AI agent to parse and use, earning a top score of 5.

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

Completeness3/5

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

Given the tool's complexity (moderate, involving comparison and savings analysis), no annotations, no output schema, and 100% schema coverage, the description is minimally adequate. It explains the core function but lacks details on output format, error handling, or integration with siblings. Without annotations or output schema, more context on behavioral aspects would improve completeness, but it meets the basic threshold for a score of 3.

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

Parameters3/5

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

The description adds no parameter semantics beyond what the input schema provides. The schema has 100% description coverage, clearly documenting the single parameter 'time_range' with its enum values and default. Since the description doesn't elaborate on parameter usage (e.g., how time_range affects the comparison), the baseline score of 3 is appropriate, as the schema adequately handles parameter documentation.

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 the tool's purpose: 'Compare actual spend against optimal routing' specifies the verb (compare) and resources (actual spend vs optimal routing). It distinguishes from siblings like 'volt_get_spend' (which likely shows raw spend) and 'volt_recommend_route' (which likely suggests routes). However, it doesn't explicitly differentiate from all siblings, such as 'volt_check_price' or 'volt_set_budget_alert', keeping it at a 4 rather than a 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It mentions 'Shows savings achieved and savings missed' but doesn't specify contexts, prerequisites, or exclusions. For example, it doesn't indicate if this is for post-analysis or real-time monitoring, or when to choose it over 'volt_get_spend' or 'volt_recommend_route'. This lack of explicit when/when-not/alternatives results in a score of 2.

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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