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List the user's recent campaign drafts

list_campaign_drafts
Read-onlyIdempotent

Return recent campaign drafts on this Upfixe account, newest first. Useful for: • Recovering from a dropped connection during generate_campaign_draft — the work finishes server-side even if the LLM never gets the response, so the draft will be here. • Answering 'what drafts do I have for brand X?' or 'show me my campaigns'. • Picking up where the user left off in a previous session.

Returns brandId, draftId, name, status, createdAt, and a 1-line summary (ad-group count + total keywords + total headlines). To see full contents, follow up with inspect_campaign_draft({ draftId }).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax drafts to return, newest first. Default 10, max 50.
brandIdNoFilter to drafts for a specific brand. Omit to see drafts across all brands on this account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the read-only/idempotent safety profile, but the description adds genuinely non-obvious behavior: generation completes server-side even when the LLM never receives the response, and it enumerates the returned fields (brandId, draftId, name, status, createdAt, summary). It does not discuss pagination beyond the schema's limit, so it is not fully exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core action and ordering, then uses bullets for use cases and a closing sentence for return fields and follow-up. Slightly verbose and the bullet formatting has awkward mid-sentence line breaks, but every element carries 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?

With no output schema, the description compensates by enumerating the returned fields and pointing to the follow-up tool for full detail. An agent has everything needed to call this correctly and to know what comes back.

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?

Schema description coverage is 100%, so both limit and brandId are already documented with defaults, bounds, and the omit-to-see-all-brands behavior. The description only echoes brand filtering in prose ('drafts for brand X') and adds no syntax or format detail beyond the schema.

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 plus scope and ordering: 'Return recent campaign drafts on this Upfixe account, newest first.' It also implicitly distinguishes itself from inspect_campaign_draft, which it names as the tool for full contents.

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 three concrete when-to-use scenarios (recovering from a dropped generate_campaign_draft call, answering brand/campaign questions, resuming a prior session) and explicitly routes to inspect_campaign_draft({ draftId }) when full contents are needed. Nothing is left to inference.

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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