campaignstack_list_automations
List scheduled automations for a campaign. Shows automation name, schedule, enabled status, and last run outcome.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| campaignId | Yes |
List scheduled automations for a campaign. Shows automation name, schedule, enabled status, and last run outcome.
| Name | Required | Description | Default |
|---|---|---|---|
| campaignId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds meaningful context beyond those annotations by specifying exactly what information is shown: automation name, schedule, enabled status, and last run outcome. This is especially valuable since there is no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. The first sentence states the purpose, and the second lists the output fields. Everything included earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple: one required parameter, read-only, safe, and idempotent. The description covers the output fields despite the missing output schema. It does not mention pagination or empty-result behavior, but for a straightforward list operation the provided context is largely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 does tie the single parameter to the campaign by saying 'for a campaign', but it does not explain the format or origin of campaignId beyond the schema's minLength constraint. This is adequate but leaves a gap for an agent unfamiliar with the platform.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and a specific resource ('scheduled automations for a campaign'), and it names the key output fields. It is clear about what the tool returns, though it does not explicitly differentiate itself from nearby siblings like campaignstack_get_automation_jobs or campaignstack_list_workflows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool: when you need to see a campaign's scheduled automations and their status. It does not mention alternatives or exclusions, but the scoping to a campaign and the read-only listing purpose provide enough contextual guidance for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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).