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campaignstack_get_draft_checkup

Read-onlyIdempotent

Get the workspace's open draft checkup proposal, or null when none is pending. A checkup analyzes recent AI drafts plus review decisions (edits and rejections) and proposes ONE change to the workspace's craft data: an outreach-intent detail, a playbook section, or the offer context. The result carries the named findings with evidence, the current vs proposed text, and before/after replays of real drafts under the proposed text. Nothing is applied until campaignstack_accept_draft_checkup.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdNoDefaults to the API key's workspace

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already mark it read-only, idempotent, and non-destructive; the description adds valuable behavioral detail: it returns null when no proposal is pending, describes the contents of the result (findings with evidence, current vs proposed text, before/after replays), and emphasizes that no changes are applied until the accept sibling is invoked. This goes well beyond the structured annotations.

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 four sentences, front-loaded with the core purpose, and each sentence adds distinct information: what is returned, what a checkup is, what the result contains, and the side-effect boundary. 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?

With no output schema, the description carries the burden of explaining the return value, and it does: null when none pending, named findings with evidence, current vs proposed text, and before/after replays. The single workspaceId parameter is covered by schema, and annotations cover safety, so nothing essential is missing for an agent to call this correctly.

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?

There is only one optional parameter, and the schema already documents its default behavior ('Defaults to the API key's workspace'). Schema description coverage is 100%, so this is the baseline case where the description does not need to add parameter-level detail, and it doesn't.

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?

Description opens with a specific verb and resource: 'Get the workspace's open draft checkup proposal, or null when none is pending.' It further defines what a checkup is and distinguishes the read-only nature from accept by noting 'Nothing is applied until campaignstack_accept_draft_checkup.' This is unambiguous and sets it apart from sibling accept/reject/run tools.

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?

Description makes it clear this is the retrieval action for a pending proposal and explicitly warns that nothing is applied until the accept sibling is called. It does not explicitly name run_draft_checkup as the action that generates a proposal, so the when-to-use guidance is good but not exhaustive.

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).

Resources