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shopify-chatgpt-ads-mcp

shopify-chatgpt-ads-mcp

by Avada-AI

Pause campaign

pause_campaign

Stop a campaign from delivering ads by pausing it with its campaign ID; no confirmation is needed, and you can reactivate it later.

Instructions

Pause a campaign: it stops delivering. Safe; no confirmation needed. Undo with activate_campaign (which asks first).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "campaign_id": "<campaign_id>"
    },
    "name": "pause_campaign"
  }
}

Input Schema

NameRequiredDescriptionDefault
campaign_idYesCampaign id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false, and the description reinforces this while adding the non-obvious facts: the concrete effect (delivery stops), no confirmation prompt, and a named reversible path. It does not mention permissions, error behaviour, or what happens to in-flight delivery, so it is strong but not exhaustive.

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?

Three short clauses in one compact line, front-loaded with the effect and followed by safety and the reversal path. Nothing is redundant or buried.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter mutation with a full annotation set and no output schema, the definition covers effect, safety, and undo. The only real gap is precondition/error behaviour (e.g., pausing an already-paused campaign), which an agent might want before calling.

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 a single parameter, campaign_id, and schema coverage is 100% with a pattern constraint, so the schema carries the semantics. The description adds nothing about the id itself (source, format, or whether ids from list_campaigns are accepted), so the baseline of 3 applies.

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?

"Pause a campaign: it stops delivering" gives a specific verb (pause), a specific resource (campaign), and the operational effect (delivery stops). Combined with the pointer to activate_campaign, an agent can distinguish this from archive_campaign and the ad-level pause tools without opening a schema.

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?

It tells the agent this action needs no confirmation and names activate_campaign as the reverse operation, including the asymmetry that activate asks first. That is actionable context, but it doesn't state any precondition or when-not condition (e.g., what happens pausing an already-paused or archived campaign).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.