TrueClicks

Campaign-level audit rule results

audit_rule_result_campaign

Read-only

Get campaign-level audit rule results as a Markdown summary. Single account only (not cross-account). Included: campaigns that are currently failing (have output rows in the latest audit run) AND, when numberOfWeeks > 0, campaigns that were failing in any historical week but are now resolved (shown with "Rows (0)" in the current column). Not included: campaigns that passed in both the current run and all historical weeks (no output rows at any point). Only rules where IsCampaignSpecific = Yes are considered. Cell values in historical week columns: an actual result means the rule ran and found issues; "Rows (0)" means the rule ran and calculated results for that campaign but found nothing (passed); "-" means the rule did not run at all that week.

Input Schema

TableJSON Schema

Name	Required	Description
`accountId`	Yes	Single TrueClicks account id (the numeric Id field from the account listing, not the platform customer id).
`campaignIds`	No	Campaign IDs to filter results. Only rows with matching CampaignId are returned. If null or empty, all campaigns are returned.
`numberOfWeeks`	No	Number of historical weeks to include (e.g. 4 = last 4 weeks) alongside current results. Default 0 returns current results only.

Schema Changelog

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

Changed1 schema field changedSep 7, 2026

changedInput schema / properties / accountId / description

Previous value: -"Single account Id"New value: +"Single TrueClicks account id (the numeric Id field from the account listing, not the platform customer id)."

First observedSep 7, 2026

TDQS

A4/5.0

Behavior4/5

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

Beyond the read-only annotation, the description discloses the exact behavior regarding historical weeks, how results are filtered, and the meaning of cell values like 'Rows (0)' and '-'. It provides substantial operational details that an agent would need to interpret the output correctly.

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

Conciseness3/5

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

The description is verbose and repeats inclusion/exclusion logic in multiple places. While it is well-structured and front-loaded, the redundant clarifications could be condensed without losing meaning, making it less concise than ideal.

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?

The description covers the output format (Markdown summary), the inclusion rules, and the interpretation of historical data. It does not mention pagination or error handling, but for a read-only reporting tool, the provided context is largely sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters have descriptions that go beyond type definitions. For example, campaignIds explains the filtering behavior and the null/empty default, and numberOfWeeks clarifies the default and its effect. This provides clear semantic value 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?

The description clearly states that the tool gets campaign-level audit rule results as a Markdown summary, and explicitly distinguishes it from account-level or rule-level results. It also defines the inclusion and exclusion criteria, making the purpose unambiguous.

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

Usage Guidelines3/5

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

The description explains the scope (single account, campaign-specific rules) and the inclusive/exclusive logic, but it does not explicitly compare this tool to sibling tools like audit_rule_result or audit_account_result. The selection is implied by the title and content, but not directly stated.

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

A3.9/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, but the audit and report tools (e.g., audit_rule_output_table vs audit_rule_output_table_historical vs audit_rule_result vs audit_rule_result_campaign) are closely related and rely on detailed descriptions to differentiate.

Naming Consistency4/5

Naming is generally consistent with snake_case and domain-prefixed groups (google_ads_*, ms_ads_*, perfmon_*), though a few tools are bare nouns (account, task, user) rather than verb-led, which slightly deviates from the dominant pattern.

Tool Count4/5

23 tools is on the higher end but justified for a platform covering multiple ad platforms, audit reports, alerts, and user management; it remains navigable with clear groupings.

Completeness4/5

The tool set comprehensively covers account enumeration, audit results, report execution for major ad platforms, perfmon alerts, pacing targets, tasks, and users. Minor gaps exist (e.g., no create/update/modify operations), but the core analytics and monitoring surface is well covered.

Resources

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