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campaignstack_cancel_node_leads

DestructiveIdempotent

Cancel the drainable leads at a workflow node (WAITING, WAITING_FOR_EVENT, PENDING_REVIEW entries are marked cancelled). PROCESSING leads have a live runner job and are left to finish on their own; the response reports how many remain. Use this to drain a node that campaignstack_update_workflow or a node deletion rejected with NODE_HAS_ACTIVE_LEADS, then retry the graph change. Use campaignstack_get_workflow to find node IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodeIdYes
workspaceIdYes

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?

The description adds meaningful behavior beyond the annotations: it explains which lead states get cancelled, which are left to finish, and that the response reports how many remain. With destructiveHint and idempotentHint already present, this nuanced partial-cancellation behavior is exactly the extra context an agent needs.

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?

Three dense sentences front-load the effect, then provide the exception, then give the trigger context and lookup pointer. There is no filler or repetition of schema/annotation information.

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 destructive operation with no output schema, the description covers what will be cancelled, what won't, what the response indicates, when to use it, and how to find required IDs. Nothing critical is missing for an agent to decide to call it and interpret the result.

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 description coverage is 0%, so the description must compensate. It indirectly explains nodeId by describing workflow nodes and telling the agent to use campaignstack_get_workflow to find node IDs, but it never mentions workspaceId or how to obtain it, leaving one of the two required parameters only inferable from its name.

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 action and resource: 'Cancel the drainable leads at a workflow node', then defines which entries are affected (WAITING, WAITING_FOR_EVENT, PENDING_REVIEW) and which are not (PROCESSING). This distinguishes the tool from workflow-update/delete and node-inspection siblings, so an agent can identify when this tool applies.

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?

It gives an explicit trigger: use it to drain a node when campaignstack_update_workflow or a node deletion fails with NODE_HAS_ACTIVE_LEADS, then retry the graph change. It also states what to expect for PROCESSING leads and points to campaignstack_get_workflow for finding node IDs, which is concrete routing guidance.

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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