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TrueClicks

by com.trueclicks

Audit rule output table (historical)

audit_rule_output_table_historical
Read-only

Get the detailed output rows for one or more audit rules across multiple historical weeks for one account, as a multi-block CSV: one ">>>>> RuleKey: ..., Week: yyyy-MM-dd" block per rule/week, each followed by a "metadata: { tooltip: {...} }" line and that rule/week's rows as CSV. Use to compare how findings changed over time. Weeks are identified by their Monday start date. Weeks with no completed run for a rule contribute no block.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional maximum rows per rule per week.
ruleKeysYesOne or more audit rule key strings, e.g. "QueryMining_InefficientNGrams".
accountIdYesTrueClicks account id to retrieve results for (the numeric Id field from the account listing, not the platform customer id).
campaignIdsNoOptional campaign IDs to filter rows per rule per week. Omit or leave empty to return all rows.
weekStartDatesYesMonday week-start dates (yyyy-MM-dd) identifying the weeks to retrieve.

Schema Changelog

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

  1. Changed1 schema field changed
    • 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)."
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly annotation, the description discloses the exact output behavior: multi-block CSV with block headers, metadata lines, and omission of missing weeks. This transparently sets expectations for retrieval results without contradicting the annotations.

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?

The description is well-structured and concise, delivering the tool's purpose, output format, and edge-case behavior in four short sentences. No filler or redundant phrases dilute the message.

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?

Since there is no output schema, the description provides enough detail about the response shape: block format, metadata line, CSV rows, and behavior for missing weeks. Combined with the complete parameter descriptions, an agent can understand the tool's functionality without ambiguity.

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?

The input schema already covers 100% of parameters with clear descriptions, including accountId, ruleKeys, weekStartDates, optional campaignIds, and limit. The description does not add significant parameter-specific meaning beyond the schema, so a baseline score is appropriate.

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 states a specific verb 'Get' and resource: detailed audit rule output rows for one or more rules across multiple historical weeks. It clearly distinguishes historical retrieval from current output tables by emphasizing the multi-block historical CSV format and time comparison purpose.

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?

The description explicitly says 'Use to compare how findings changed over time,' giving a clear when-to-use directive. It also clarifies week identification by Monday start dates and behavior for weeks with no completed run, which helps the agent know when to call this tool.

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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