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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
workspaceIdNoWorkspace ID (required for user keys; workspace keys are bound)

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / properties / workspaceId / description
      Previous value: -"Defaults to the API key's workspace"New value: +"Workspace ID (required for user keys; workspace keys are bound)"
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, and the description adds substantial behavior beyond them: it returns null when none is pending, describes the analysis inputs, the single-change proposal, the result contents (findings with evidence, current vs proposed text, before/after replays), and explicitly states nothing is applied. This is rich, non-obvious behavioral disclosure.

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 with no filler. It front-loads the core action and null behavior, then adds necessary context about what a checkup is and what the result contains. Every sentence contributes distinct 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?

Given the simple single-parameter schema, rich annotations, and no output schema, the description is complete enough for an agent to call this correctly. It explains the return value, the null case, the result shape, and the non-applying behavior, so no critical operational information is missing.

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?

The only parameter, workspaceId, is fully described in the input schema, including the user-key vs workspace-key nuance. The description does not add new parameter-level details, so the schema carries the semantic weight; therefore baseline 3 is appropriate.

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 starts with a specific verb and resource: 'Get the workspace's open draft checkup proposal,' and adds the null-when-pending behavior. It clearly distinguishes this from accept/run/reject siblings by describing what the checkup is and noting that nothing is applied until campaignstack_accept_draft_checkup.

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?

The description makes clear this is the read-only retrieval counterpart and explicitly references accept_draft_checkup as the mutating follow-up. It does not fully enumerate when to prefer this over run_draft_checkup or reject_draft_checkup, but the read-only framing plus 'open draft checkup proposal' provides strong contextual 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.

Resources