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by io.github.getanyapi-com
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Quote a price

quote_api
Read-only

Get the exact price of a run_api call BEFORE running it - free, no key required, nothing is charged or executed. Pass the same sku_id and input you would give run_api: the quote resolves pricing exactly as the run will, and also validates your input against the API schema so you catch invalid_input for free. Returns maxCostUsd (the ceiling reserved), minCostUsd (the likely charge), and the base/per-item breakdown explaining why they differ. These are amounts this one call is charged, not catalog comparison rates: report them as-is and never scale them to 1,000 requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesthe exact input payload you plan to pass to run_api; the quote resolves pricing the same way the run will
sku_idYesthe API SKU slug to price
contextYesExplain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
exactYestrue when the price is exact (minCostUsd == maxCostUsd): a flat SKU or a sealed page
baseUsdYesfixed cost per call in USD, charged regardless of count
pricingYesa one-line human explanation of how this call is priced
maxCostUsdYesthe most this call can charge - the reserve held before running
minCostUsdYesthe likely charge - the cheapest route serves first
perItemUsdYesmarginal cost in USD per billable unit (see perItemUnit); 0 for a flat SKU
perItemUnitNothe unit perItemUsd is charged per: 'result' (default) or an input unit like 'username' for input-priced SKUs

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "sku_id",
-  "input"
-]New value: +[
+  "sku_id",
+  "input",
+  "context"
+]
  2. Added

TDQS

A4.7/5.0
Behavior4/5

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

The description goes beyond the annotations by disclosing that the quote is free, requires no key, does not execute or charge anything, and resolves pricing exactly as the run will. It also explains that it validates input against the API schema and returns specific cost fields with their meanings. Since readOnlyHint=true is already present, the description adds valuable context without contradicting it, though it doesn't detail every edge case.

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 compact, front-loaded with the most important fact (free, no key, no charge/execute), and every sentence adds value: usage caveat, validation benefit, return fields, and a critical scaling warning. It is well-structured and avoids redundancy despite covering several key details.

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?

For an agent deciding whether and how to invoke this tool, the description covers the necessary context: when to use it, what inputs to provide, what it returns, and what not to do with the results. With a full input schema and output schema, nothing critical is missing.

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?

Schema description coverage is 100%, so the schema already documents each parameter. The description adds meaning by explaining that sku_id and input must match exactly what would be passed to run_api, and it gives context for the returned cost fields. It reinforces the relationship between parameters and tool behavior, though it doesn't describe the context parameter in detail beyond the schema.

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

Purpose5/5

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

The description is specific and action-oriented: it states the tool quotes pricing for a run_api call before execution, with no charge or execution. It distinguishes itself from siblings like run_api and read_result by focusing on pre-run pricing, and explicitly mentions validation, making its purpose unmistakable.

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

Usage Guidelines5/5

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

The description explicitly tells the agent to use this tool BEFORE running run_api, to pass the same sku_id and input as intended for run_api, and to catch invalid_input for free. It also warns against scaling the quoted amounts to 1,000 requests, which is a clear usage boundary. This effectively separates it from run_api and other siblings.

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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