campaignstack

campaignstack_get_exclusions

Read-onlyIdempotent

Get who a workspace may never contact. Exclusions have two levels and combine by union: level 0 is the workspace list every campaign and signal agent honours, level 1 is a per-consumer extra that can only add to it. level=workspace (default) returns the level-0 entries with their enabled status and config. level=effective, with signalAgentId or workflowId, returns level 0 merged with that consumer's own entries, which is the set the pipeline applies. Read that one to explain why a lead was skipped. Use exclusionId values with campaignstack_list_manual_exclusion_urls, campaignstack_add_manual_exclusion_urls, campaignstack_remove_manual_exclusion_url, or campaignstack_toggle_exclusion. Use campaignstack_list_signal_agents to find signal agents for context.

Input Schema

TableJSON Schema

Name	Required	Description
`level`	No	workspace (default) returns the level-0 list alone. effective returns level 0 merged with the level-1 extras of the consumer named by signalAgentId or workflowId, which is what the pipeline applies.
`workflowId`	No	With level=effective, merge this workflow source node's own exclusions
`workspaceId`	No	Defaults to the API key's workspace
`signalAgentId`	No	With level=effective, merge this signal agent's own exclusions

Schema Changelog

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

First observedSep 4, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the readOnly/idempotent/destructive-safe annotations, the description reveals important behavioral semantics: the two-level union model, that level 1 can only add to level 0, that effective merges both levels, and that this merged set is what the pipeline applies. This gives the agent a clear model of tool behavior.

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 every sentence earns its place: purpose, level model, parameter behavior, return contents, and sibling routing. No filler or redundancy.

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 read-only lookup tool with no output schema, it adequately describes what each level returns (entries with enabled status/config, merged sets), which parameters are needed, and how results connect to related tools. Nothing essential 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. The description adds meaning by explaining the union relationship between levels, the 'only adds' constraint, and the practical reason to request effective exclusions. This exceeds the schema without fully redefining parameter formats.

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 who a workspace may never contact') and then precisely defines the two exclusion levels. This distinguishes the tool from siblings like toggle_exclusion or set_agent_exclusions without requiring schema inspection.

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 explicitly explains when to use level=workspace vs level=effective, and routes the agent to related tools for exclusionId-based mutations and for finding signal agents. The note to read level=effective to explain why a lead was skipped is a concrete, actionable usage guideline.

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).

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