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Get an AI new-campaign draft

get_campaign_draft
Read-onlyIdempotent

Returns the state of a draft started by draft_campaign: pending, running, done or failed. When done, campaign can be passed verbatim to create_search_campaign (preview first). If missing_fields is not empty (usually campaign.daily_budget), ask the user, set those fields on campaign, then preview. When failed, error explains why; start a new draft. Drafts are kept for 24 hours.

Input Schema

NameRequiredDescriptionDefault
draft_idYesdraft_id returned by draft_campaign.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, but the description adds genuinely non-structured behavior: a 24-hour retention window, the fact that failed states carry an explanatory error, and the missing_fields remediation flow. These are lifecycle and recovery facts an agent cannot get from annotations or schema.

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?

Front-loads the return contract (the four states) before the action guidance, and every sentence carries load: state enumeration, happy-path routing, missing-field handling, failure handling, TTL. No filler.

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?

No output schema exists, yet the description fully covers what comes back (state names, campaign payload, missing_fields, error text) and what to do in each case. For a single-parameter polling tool this leaves nothing an agent needs 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?

Only one parameter exists with 100% schema description coverage; the schema already says draft_id is 'returned by draft_campaign'. The description reinforces the linkage to draft_campaign but adds no format or constraint detail beyond the schema, so the 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?

States a specific verb and resource ('Returns the state of a draft started by draft_campaign') and enumerates the exact possible states (pending, running, done, failed). This clearly distinguishes it from siblings like draft_campaign (which creates the draft) and get_ad_group_draft (a different draft type).

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?

Gives explicit branch-by-branch guidance: when done, pass campaign verbatim to create_search_campaign after previewing; when missing_fields is non-empty, ask the user and set fields; when failed, read the error and start a new draft. This is a full decision tree for the agent, not just a use context.

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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