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Glama

TrueClicks

by com.trueclicks

Execute Microsoft Ads bulk query

ms_ads_execute_bulk_query
Read-only

Execute a Microsoft Ads bulk query for one account, returning entity/configuration rows as TSV (tab-separated, header row + one row per line). This is an entity/configuration snapshot with no date range or aggregation, as opposed to time-bound performance metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reportYesMicrosoft Ads bulk report name.
columnsYesReport columns to select.
accountIdYesTrueClicks account id (the numeric Id field from the account listing, not the Microsoft customer id / ClientCustomerId). Must be a Microsoft account accessible by the connector.

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 query (must be a Microsoft account accessible by the connector)."New value: +"TrueClicks account id (the numeric Id field from the account listing, not the Microsoft customer id / ClientCustomerId). Must be a Microsoft account accessible by the connector."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

The readOnlyHint and destructiveHint annotations already indicate safety, and the description reinforces a read-only snapshot behavior by describing the TSV output and lack of date aggregation. It adds useful context about the output format and data scope.

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 two sentences with no redundant wording. It front-loads the primary action and resource, then clarifies output format and scope in a compact way.

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?

Given there is no output schema, the description sufficiently indicates the return format (TSV with header row). It also explains the snapshot nature and what the data represents, covering the main context needed for correct use.

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?

All three parameters are described in the schema with 100% coverage, so the description adds minimal additional parameter-level meaning. The existing parameter descriptions are adequate for understanding report name, columns, and account ID.

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 executes a Microsoft Ads bulk query for one account and returns entity/configuration rows in TSV format. It explicitly contrasts with time-bound performance metrics, distinguishing it from sibling reporting tools.

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 provides direct guidance on when to use this tool: for entity/configuration snapshots with no date range or aggregation, as opposed to time-bound performance metrics. This makes the appropriate context clear relative to the available alternatives.

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