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campaignstack_list_lead_lists

Read-onlyIdempotent

List all lead lists in a campaign with lead count per list. Returns type (set or query) and source for each list. Use the returned leadListId values with campaignstack_get_lead_list or campaignstack_add_leads_to_list. Use campaignstack_list_campaigns to find valid campaign IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaignIdYes

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the description only needs to add context beyond those. It does so by stating that the tool returns lead count, list type (set or query), and source for each list. It does not mention pagination or a full return schema, but that is a minor gap for a simple read-only enumeration.

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 three sentences with the main function front-loaded, followed by return details and related-tool guidance. Every sentence earns its place, and 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?

For a one-parameter read-only tool whose annotations already cover the safety profile, the description is complete: it states what is listed, what fields are returned, and how to obtain both campaignId and leadListId. The absence of pagination details is acceptable given the simple scope.

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?

The schema has one required campaignId parameter with 0% description coverage, so the description must compensate. It only indirectly defines the parameter by saying 'in a campaign' and by directing users to campaignstack_list_campaigns to find valid campaign IDs. This is helpful but lacks explicit format, examples, or a direct statement of what campaignId represents.

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 'List all lead lists in a campaign with lead count per list', clearly stating the verb, resource, and scope. It also specifies the returned attributes (type and source), and distinguishes this from related tools by anchoring it to a campaign and pointing to campaignstack_list_campaigns for IDs.

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?

The description gives explicit chaining guidance: 'Use the returned leadListId values with campaignstack_get_lead_list or campaignstack_add_leads_to_list' and 'Use campaignstack_list_campaigns to find valid campaign IDs.' It does not explicitly contrast this tool with siblings like campaignstack_list_external_lead_lists, but the campaign scoping and next-step routing provide clear usage context.

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

A3.7/5.0
Disambiguation3/5

The set is enormous and generally well-differentiated through detailed cross-referenced descriptions, but several clusters blur together: archive/delete/remove have inconsistent permanence semantics (delete_campaign vs remove_signal_watch vs archive_campaign), create_connection_watch_agent explicitly overlaps with set_account_watcher, and the parallel draft-checkup and playbook-proposal flows (run_draft_checkup/get_draft_checkup/accept_draft_checkup vs propose_playbook_change/get_playbook_proposal/decide_playbook_proposal) present near-identical decision pipelines.

Naming Consistency4/5

Nearly every tool follows the campaignstack_<verb>_<noun> convention with disciplined get/list pairing and consistent verb choices (create/update/delete/pause/resume). Minor deviations like campaignstack_priority_enrich (adverb+verb) and campaignstack_whoami break the strict verb_noun pattern but are isolated and do not hinder navigation.

Tool Count1/5

223 tools is an extreme surface for any MCP server. Even though each tool maps to a distinct API operation and the underlying platform is broad, the scale far exceeds the 50+ threshold for an extreme mismatch and will overwhelm agents with selection overhead.

Completeness5/5

The surface is exhaustive for the LinkedIn outreach domain: full campaign/workflow/lead-list lifecycles, ICP and persona management, content scheduling and approvals, inbox and messaging, enrichment and integrations, signal watches and exclusions, review queues, playbook versioning, workspace admin, billing, and notifications. Minor gaps like a missing delete_lead or delete_company are explained by shared-data semantics, so no critical dead ends remain.

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