Soundcheck Live Event Quotes

Estimate event cost (illustrative)

quote_event

Read-only

Returns a ballpark cost, budget range, or line-item needs estimate for a live event (party, birthday, wedding, corporate offsite, conference, concert, festival, gala, fundraiser, and similar). No login. Takes a plain-language description (for example "rooftop birthday in Austin Friday night for 50 people with a DJ and tacos") and returns an illustrative low/mid/high estimate, line-item breakdown (labor, production, add-ons, logistics), suggested deposit, assumptions, confidence, missing information, and evidence pointers. Numbers come from the versioned SYNTHETIC pricing catalog and a deterministic engine — not model-invented prices. The catalog is illustrative: not real cost of goods and not a binding vendor quote (request_booking contacts an organization for a binding price). A returned quote_id plus overridden requirements refines an estimate. Optional use_ai_grounding (default off) may fill only event type, location, and date; it never supplies a number; the pasted text is sent to a third-party AI provider, Anthropic (Claude), through the Vercel AI Gateway with zero-data-retention routing requested; Soundcheck does not save it to any event or account (https://soundchecklive.io/privacy).

Input Schema

TableJSON Schema

Name	Required	Description
`date`	No	event day (YYYY-MM-DD)
`location`	No	city, metro, or venue name used to resolve the market index
`quote_id`	No	a quote_id from an earlier quote_event call, to refine instead of starting over
`date_range`	No	multi-day run as civil days (YYYY-MM-DD)
`description`	No	free-text event description, e.g. "Two-day outdoor music festival in Austin, ~3,000 attendees, LED wall and livestream". Required unless quote_id is given.
`requirements`	No	structured overrides; they win over anything read from the description
`use_ai_grounding`	No	opt in to one AI normalization pass that may fill ONLY event type, location/venue, and date. Never supplies a number. Default false. When true, the pasted text is sent to a third-party AI provider, Anthropic (Claude), through the Vercel AI Gateway with zero-data-retention routing requested; Soundcheck does not save it to any event or account (https://soundchecklive.io/privacy).

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	true on success (including confirmation_required prompts)
`data`	No	tool payload (API/composite/confirmation object); object, array, or primitive JSON
`error`	No	when ok is false

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 1, 2026

changedInput schema / properties / use_ai_grounding / description

Previous value: -"opt in to one AI normalization pass that may fill ONLY event type, location/venue, and date. Never supplies a number. Default false."New value: +"opt in to one AI normalization pass that may fill ONLY event type, location/venue, and date. Never supplies a number. Default false. When true, the pasted text is sent to a third-party AI provider, Anthropic (Claude), through the Vercel AI Gateway with zero-data-retention routing requested; Soundcheck does not save it to any event or account (https://soundchecklive.io/privacy)."

First observedSep 26, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Goes well beyond the readOnly/destructive/openWorld annotations: discloses that numbers come from a versioned synthetic catalog plus deterministic engine rather than model invention, that results are not real COGS, and that optional AI grounding sends text to Anthropic via Vercel AI Gateway with zero-data-retention and no storage. That is exactly the extra behavioral context annotations cannot convey.

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

Conciseness4/5

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

Front-loads purpose and example, then layers disclaimers and privacy detail. The AI/privacy sentence duplicates the use_ai_grounding schema description nearly verbatim, which is slight redundancy, but the density is justified for a compliance-sensitive estimator.

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 a 7-parameter, nested-schema tool with an output schema, the description covers the workflow contract (description or quote_id required, requirement overrides, refinement, grounding opt-in) and return-shape expectations; nothing material is left for the agent to guess.

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 coverage is 100%, so the baseline is 3; the description earns an upgrade by explaining the interaction between quote_id and requirements (refine vs start over) and clarifying that structured requirements win over the description text, which the schema fields alone only hint at.

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?

States a specific verb+resource (returns a cost/budget estimate for a live event) and immediately scopes it as illustrative/ballpark, with a concrete enumeration of event types and an example input. It also distinguishes itself from the sibling request_booking by noting that tool handles a binding vendor price.

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

Usage Guidelines4/5

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

Clearly frames itself as an illustrative estimate and points to request_booking for a binding quote, plus explains the quote_id refinement path. It never states an explicit 'use this when...' trigger, but the when-not (not a binding quote) is effectively covered.

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

All Soundcheck Live Event Quotes tools Inspect

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