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Thumbtack: Send estimate

thumbtack_send_estimate

Thumbtack: Send an estimate in the conversation with line items, discount and tax. Sends an estimate in the lead's conversation with custom line items, an optional discount, tax and a message to the customer. The total is computed from the line items. Thumbtack cannot cancel a sent estimate; send a new one to correct it. By default you confirm each call; you can switch that off for this tool. Reaches other people: confirm with the user before each call. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lead_idYesLead ID from list_leads.
messageNoNote to the customer.
discountNo{ type: percent or amount, value }.
line_itemsYesList of { name, unit, quantity, unit_price }.
tax_percentNoTax rate in percent.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only carry the generic safety profile (not read-only, open-world, non-destructive), while the description adds high-value behavior: an estimate is irreversible once sent, the total is derived from line items, each call is confirmed by default, and it reaches other people so user confirmation is needed. It also states the Cotlet API key/auth requirement. This is exactly the 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.

Conciseness3/5

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

The behavioral and safety sentences are front-loaded and earn their place, but the opening sentence ('Send an estimate in the conversation with line items, discount and tax') is almost verbatim repeated by the second, wasting space on restatement.

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 five-parameter write tool with no output schema, the description covers purpose, key parameters, irreversibility, confirmation behavior, and auth requirements. Nothing critical to correct invocation 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 coverage is 100%, so the baseline is 3, but the description adds a semantic rule not present in the schema: the total is computed from the line items. It also clarifies the discount is optional and that a customer-facing message is included, adding meaning beyond the field-by-field descriptions.

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 and resource ('Send an estimate') and locates it precisely 'in the lead's conversation' with line items, discount, and tax. This clearly distinguishes it from siblings like thumbtack_send_message, thumbtack_reply_to_lead, or thumbtack_list_messages without opening any schema.

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?

Gives real routing guidance: a sent estimate cannot be cancelled, so corrections require sending a new one, and the confirmation behavior can be toggled. It does not, however, explicitly compare this tool against nearby alternatives such as send_message or reply_to_lead, leaving the agent to infer when an estimate is the right artifact.

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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