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shopify-chatgpt-ads-mcp

shopify-chatgpt-ads-mcp

by Avada-AI

Change history

list_audit_logs
Read-only

Retrieve ad account change history, newest first, to see who changed what and when, with before/after values and filters for campaign, ad group, ad, or date range.

Instructions

OpenAI's record of changes in the ad account, newest first: who changed what and when, with before/after values where OpenAI records them. MEASURED: changes made through an API key are attributed to the key's owner, the same as that person's own Ads Manager changes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_audit_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
ad_idNoAd id
afterNo
limitNo
sinceNoISO date or time
untilNoISO date or time
ad_group_idNoAd group id
campaign_idNoCampaign id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so safety is covered. The description adds real value beyond that: result ordering (newest first), inclusion of before/after values 'where OpenAI records them', and the non-obvious attribution rule that API-key changes are credited to the key's owner. It still omits pagination/default-limit behavior, which matters for a 7-param list tool.

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?

Two sentences, front-loaded with what the tool returns and how it is ordered; almost nothing is wasted. The 'MEASURED:' label introducing the attribution note is slightly cryptic, but the sentence it heads is genuinely informative.

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 read-only list tool with no output schema, the description covers content, ordering and an important attribution caveat, which is most of what an agent needs. The gaps are pagination/truncation behavior and how the filters combine, both relevant given seven optional parameters.

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 coverage is 71%, so the schema documents most parameters (ids, since/until, limit), giving a baseline of 3. The description adds no filter semantics of its own – it never explains how since/until or limit behave, nor what the 'after' parameter does in relation to the before/after values it mentions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (the ad account's change record) and its contents (who changed what, when, with before/after values), which is unmistakably different from the entity-listing siblings. It would earn a 5 if it explicitly framed itself as the audit/history counterpart to those listing tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use or when-not-to-use guidance, and no sibling is named as an alternative. The only steer is implicit: this is where you look for change history rather than current entity state.

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