TrueClicks

Audit rule output table

audit_rule_output_table

Read-only

Get the detailed output rows for the latest completed audit run of one or more rules for one account, as a multi-block CSV: one ">>>>> RuleKey: ..." block per rule, each followed by a "metadata: { tooltip: {...} }" line and the rule's rows as CSV. Provides the raw findings behind a failing audit rule. Rules with no completed run in the last 30 days contribute no block.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Optional maximum rows per rule (defaults to 10000 when omitted).
`ruleKeys`	Yes	One or more audit rule key strings, e.g. "QueryMining_InefficientNGrams".
`accountId`	Yes	TrueClicks account id to retrieve results for (the numeric Id field from the account listing, not the platform customer id).
`campaignIds`	No	Optional campaign IDs to filter rows. Omit or leave empty to return all rows.

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: -"Ad platform account ID to retrieve results for."New value: +"TrueClicks account id to retrieve results for (the numeric Id field from the account listing, not the platform customer id)."

First observedSep 7, 2026

TDQS

A4.1/5.0

Behavior4/5

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

The description discloses significant behavior: the output format, the rule-key block structure, and the 30-day no-run exclusion. The readOnlyHint annotation already covers the read-only nature, and the description adds no conflicting information.

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?

The description is somewhat long but well-organized and directly relevant. It front-loads the core purpose and then explains formatting, striking a balance between completeness and brevity.

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 simple read-only tool with no output schema, the description provides sufficient context: it explains the output format, the filtering condition (30-day window), and the purpose (raw findings). It does not need to elaborate on authentication or error handling given the tool's simplicity and the presence of sibling tools for historical data.

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 descriptions cover all four parameters completely, so the baseline is 3. The description does not add extra semantic detail beyond what the schema already provides, such as clarifying the relationship between accountId and campaignIds.

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 the tool's function: retrieving detailed output rows for the latest completed audit run for one or more rules. It also specifies the output format (multi-block CSV with rule keys and metadata) and distinguishes it from the historical variant by emphasizing 'latest completed.'

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?

The description mentions that it provides raw findings behind a failing audit rule and that rules with no completed run in the last 30 days are omitted, giving practical guidance. However, it does not explicitly contrast with sibling tools like audit_rule_output_table_historical, though the 'latest completed' phrasing implies the difference.

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.

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