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GoodLeads

Quote a list

quote_list
Read-onlyIdempotent

What this list costs before anyone pays: how many records name a person, and the price by grade.

Pass a saved list (`list_id`, the 8-char id in `#browse?list=<id>`) or an inline
shape (`filters` + `states`; omit `states` for every live state:
CO, CT, FL, NY, TX, VA). You get the same numbers the buy page shows a person:
`matching`, `sellable`, `verified_one`, `verified_both`, `no_channel`, `unnamed`, `facets`, `prices` (the live graded price rule +
`price_rule_version`), `quote` (present when `lane` or `cap` is given),
`exact`, `computed_at`, `quote_valid_until` (counts refresh tomorrow
morning; the quote holds until then), `per_state`, and the `_meta`
provenance block every read carries (schema_version, freshness, source,
access_level). When a count is zero by design the payload adds
`zero_reasons` — a state that never publishes the value, or a channel
asked of records too new to carry one yet: the morning after the
state posts a filing the record carries the name and mailing address;
phone and email are verified when you order. Each reason names the
widened count (`nearest_alternative`, e.g. "last 90 days: 99 with a
phone") and the filters that reach it (`alternative_filters`) — relay it
instead of a silent $0.

**Billing discipline — read before quoting money to anyone.** Only
`sellable` records — matching records whose filing names a person — are
ever billed or delivered. `matching` includes `unnamed` records with no
person to reach; it is never a billable count and must never be presented
as one. Every price line is computed from `sellable` and its grades:
name and address $0.25 per record · plus one verified phone or email $0.50 · plus both $0.70 (price rule v1; live prices always come from the summary call's `prices` block). Lanes: `all` / `best` / `contact` (`all` = every sellable record at the
name-and-address grade; `best` = each record at its own grade, verified
first; `contact` = only records with a verified phone or email — add a
`has_email` filter for emailable now, `has_phone` for callable now). Cap:
`{"type": "count|budget", "value"}` — records for count, cents for
budget. Quote the server's numbers, never arithmetic of your own.

Each `quote.lines[]` entry carries `ships` (what a record at that grade
ships with, in the buyer's words — a name-and-address record never ships a
phone or email), and the summary carries `forecast` ({checked,
phone_expected, email_expected, both_expected, basis, as_of}): how many of
the records still to find on would come back with a verified phone or email,
from our measured outcomes on comparable records — relay it with its basis.
`ceiling_cents` is the most a buyer can be charged: today's total plus the forecast upgrades, charged only for what we find. Every record ships the owner's name and mailing address plus the business facts — the business name, entity type and status, the state filing number and formation date, the industry with its NAICS, SIC and Google Business codes, the registered agent, the Lead Reference, and the Reachability, Contact Relevance and Contact Confidence scores; open the exact file before paying (ten made-up records, every column): https://app.goodleads.club/api/v1/commerce/sample-file?format=xlsx (or format=csv).

The close is two questions: put the quoted choice in front of your human
— callable now (a verified phone), emailable now (a verified email, verified
for deliverability and recent activity), or newest, mail-first — plus a
standing order, then hand over the payment link for the one chosen — per
record, no minimums, so a small first order is the normal first step.

Next: to buy exactly what was quoted, hand the same list / shape, lane and
cap to `checkout_list`.

Args:
    list_id: A saved list id. Mutually exclusive with `states` / `filters`.
    states: State codes for an inline shape; omit for every live state.
    filters: Filter clauses in the one contract (see `list_filterable_fields`).
    include_held: Include inactive-or-holding entities (default False).
    lane: `all` / `best` / `contact` — asks for a `quote`.
    cap: `{"type": "count|budget", "value": <int>}` — the dial the quote
        is solved against.

Returns:
    The summary contract described above. Keyless callers may not filter
    on `contact_name`, `email_primary`, `phone_primary` (422).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
capNo
laneNo
statesNo
filtersNo
list_idNo
include_heldNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare read-only and idempotent; the description adds extensive behavioral context: quote_valid_until freshness, zero_reasons with nearest_alternative, forecast basis, ceiling_cents, and the rule that only sellable records are billed. It also warns 'Quote the server's numbers, never arithmetic of your own.' This goes far beyond the annotations and does not contradict them.

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?

The description is long but front-loaded with a one-line summary and then organized into billing, return fields, and args. There is some extra sales-oriented prose (e.g., 'The close is two questions...') that goes beyond operational necessity, making it slightly less concise than it could be, but the structure is well-sectioned and each part 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?

It covers inputs, outputs, pricing, freshness, error conditions (422 for keyless callers), and points to list_filterable_fields for filter syntax. It even provides a sample file URL to inspect the exact record shape. Given the tool's complexity and 0% schema coverage, nothing an agent needs to invoke it correctly is missing.

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

Parameters5/5

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

Schema coverage is 0%, so the description fully compensates. The Args section explains each parameter: list_id mutual exclusivity, states default, filters contract, include_held default, lane allowed values, and cap structure. It also maps parameters to output behavior (e.g., 'quote present when lane or cap is given').

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 immediately states 'What this list costs before anyone pays: how many records name a person, and the price by grade.' This is a clear, specific verb (quote) plus resource (list) with a distinct scope. It also differentiates from checkout_list by saying 'to buy exactly what was quoted...', so an agent can tell quote from purchase.

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 gives explicit when-to-use scenarios: pass a saved list or an inline shape, omit states for all live states, use lanes/ caps. It even names the alternative for the next step: 'hand the same list / shape, lane and cap to checkout_list.' It also includes a warning about billing discipline and what not to present, making usage boundaries clear.

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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