Reject the pending draft checkup without applying anything. Two consecutive rejections pause automatic checkups for 30 days (manual runs stay available).
| Name | Required | Description | Default |
|---|---|---|---|
| checkupId | Yes | Pending checkup id from campaignstack_get_draft_checkup | |
| workspaceId | No | Defaults to the API key's workspace |
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?
Beyond the annotations, the description discloses a non-obvious behavioral consequence: two consecutive rejections pause automatic checkups for 30 days while manual runs remain available. This is valuable context not carried by annotations. It does not fully describe the fate of the rejected checkup, but the key side-effect is transparent.
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 concise sentences with no wasted words. The primary action and the important consequence are front-loaded, making the description easy to parse and action.
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?
For a simple rejection action, the description provides enough information to select and invoke the tool correctly: what it operates on, the required source of the ID, and the behavioral side-effect. The lack of an output schema means return-value expectations are not addressed, but this does not block correct usage.
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 100%, and the parameter descriptions already explain checkupId's source and workspaceId's default. The tool description adds no additional parameter-level meaning, so the baseline score of 3 is appropriate.
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 clearly states the action: reject the pending draft checkup without applying any changes. This directly distinguishes it from the sibling accept_draft_checkup and clarifies the non-applying nature of the rejection.
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 gives clear context for when this tool is appropriate: when a draft checkup should be rejected rather than accepted or applied. It does not explicitly name alternatives, but 'without applying anything' and the pause side-effect provide sufficient guidance for selecting this tool over accept/run variants.
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).
