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campaignstack_get_contact_finder_request

Read-onlyIdempotent

Get one built-in Contact Finder request by id. Returns its status (queued, linked, submitted, completed, failed), what was wanted (wantEmail, wantPhone), creditsReserved at enqueue, creditsCharged once settled (reserved minus refunds, i.e. only data that was found), the result (emailFound, emailStatus, phoneFound, emailWritten, phoneWritten) and errorCode on failure. Poll it after campaignstack_enrich_lead_contact_info returned status pending with provider bettercontact; a request usually completes within minutes and never later than about an hour. Found data is already written on the lead (campaignstack_get_lead), this tool never returns the email or phone itself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestIdYesRequest id returned by campaignstack_enrich_lead_contact_info (provider bettercontact).
workspaceIdNoWorkspace ID (defaults to the bound workspace)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark this as read-only and idempotent, and the description adds substantial behavioral context beyond that: it reveals the asynchronous nature of the underlying workflow, expected completion timing ('usually completes within minutes and never later than about an hour'), the credit semantics (reserved vs charged), and the side effect that found data is written to the lead rather than returned. This is far beyond what annotations alone provide.

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 dense but efficiently structured: it leads with the operation, enumerates return fields in a logical order, then gives usage context, timing, and a critical caveat. Every sentence contributes useful information; there is no filler or repetition.

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?

With no output schema present, the description fully compensates by listing the statuses, wanted fields, credit fields, result fields, and errorCode. It also provides the trigger condition, expected duration, and the all-important clarification that the tool does not return the actual contact data. An agent has everything needed to call and interpret this tool correctly.

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?

Schema coverage is 100%, with both requestId and workspaceId already described in the input schema. The description adds no additional parameter-specific detail beyond restating the requestId origin indirectly, but with full schema coverage the baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'Get one built-in Contact Finder request by id.' It clearly distinguishes this single-request getter from the sibling list tool by deliberately saying 'one' and 'by id', and enumerates the exact fields returned, leaving no ambiguity about what the tool does.

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 guidance: 'Poll it after campaignstack_enrich_lead_contact_info returned status pending with provider bettercontact.' It also tells the agent what not to expect ('never returns the email or phone itself') and points to campaignstack_get_lead for the actual data, effectively routing to the correct sibling tools.

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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TDQS

A3.6/5.0
Disambiguation3/5

Many tools share the same verb prefix (create_, list_, update_, get_) across closely related resources, so pairs like add_lead_to_external_list vs add_lead_to_sequence, create_signal_agent vs create_signal_watch, and approve_review vs approve_content_post can be confused. The descriptions are unusually detailed and cross-referenced, which mitigates but does not eliminate the ambiguity inherent in a 282-tool surface.

Naming Consistency4/5

Virtually every tool follows the campaignstack_verb_noun snake_case pattern, which is highly predictable. Minor deviations exist: destructive operations mix remove_ and delete_ (remove_lead_list vs delete_campaign), AI generation uses both craft_ and generate_, and the seo_/search_console_ subdomains introduce a second prefix convention.

Tool Count1/5

282 tools is an extreme mismatch by any reasonable standard, exceeding the 50+ threshold by more than 5x. Even for a full B2B outreach platform, this surface is far too large and would be better consolidated into higher-level operations or grouped sub-servers.

Completeness4/5

The tool surface is impressively comprehensive, covering campaigns, workflows, leads, content, ads, SEO, integrations, billing, and more with CRUD-level depth. Minor gaps remain: no single-ICP getter, no direct pause/delete for search watches, and no explicit delete for ad campaigns (only archive via update).

Resources