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gtm_get_container

Retrieve detailed configuration for a specific GTM container using its account ID and container ID.

Instructions

Gets detailed information about a specific GTM container

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountIdYesGTM Account ID
containerIdYesGTM Container ID

Schema Changelog

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

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. The verb 'Gets' implies a read operation, but nothing else is disclosed: no failure behavior for invalid IDs, no indication of whether output includes tags/triggers/workspace data, no auth or rate-limit context. The description is essentially a paraphrase of the tool name rather than a behavioral specification.

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?

One sentence, front-loaded with the action verb, with no filler words. It is appropriately compact for a simple getter. It loses a point because the brevity comes at the cost of omitting useful context (what 'detailed information' includes), but as pure concision and structure it is well-formed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema and no annotations, the description should explain what 'detailed information' means and how to use it in the wider GTM workflow. It does neither — an agent cannot predict the return shape, the prerequisite steps (listing accounts/containers), or how this relates to gtm_get_live_version. The minimal complexity (2 params) keeps this from a 1, but the description leaves too much unspecified for a complete calling experience.

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 description coverage is 100% (both accountId and containerId have descriptions in the schema), so the baseline of 3 applies. The description adds no parameter-level meaning beyond the schema — it doesn't explain the GTM-XXXXXX format or how to obtain these IDs from sibling list tools. However, since the schema fully documents both parameters, this is acceptable and not a defect requiring compensation.

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 states a specific verb ('Gets') and resource ('detailed information about a specific GTM container'), which clearly separates it from list-style siblings like gtm_list_containers through the word 'specific'. It is also disambiguated from other get_* tools by naming the container resource. It stops short of a 5 because it doesn't explicitly name the sibling it is not, leaving some disambiguation to inference.

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?

No guidance is provided about when to use this tool versus alternatives such as gtm_list_containers or gtm_list_accounts. There is no mention of the discovery flow (calling gtm_list_accounts then gtm_list_containers to obtain the required IDs first) or any exclusions. An agent must infer usage entirely from the tool name and schema, which is a clear gap.

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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