Skip to main content
Glama

Trillboards DOOH Advertising

get_cross_channel_journey

Get cross-channel customer journey data (Sankey flow) for a campaign.

Shows how users flow between channels: DOOH -> mobile -> web -> store.

WHEN TO USE:

  • Visualizing the customer journey across DOOH and digital channels

  • Understanding channel transition patterns

  • Building Sankey diagrams of marketing funnels

RETURNS:

  • flows: Array of { source, target, count } transitions between channels

  • channels: Array of { channel, touchpoints, uniqueDevices } distribution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYesCampaign identifier

TDQS

A4.3/5.0
Behavior4/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It discloses the return structure (flows and channels arrays) and gives an example of the transition pattern, making the tool's behavior transparent. While it does not explicitly mention side effects or permissions, the 'Get' nature and the detailed return info make the operation clear.

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 with a clear first sentence, an example flow, a dedicated 'WHEN TO USE' section, and a 'RETURNS' section. Every sentence adds value, and the information is front-loaded with the core purpose. It is appropriately concise without being under-specified.

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?

Given the low complexity (one parameter, no output schema, no annotations), the description is highly complete. It explains what the tool does, provides usage scenarios, and details the return format, which covers all necessary context for an agent to select and invoke the tool correctly.

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 describes campaign_id as 'Campaign identifier' with full coverage. The description's mention of 'for a campaign' adds minimal semantic value beyond schema, essentially restating it. There is no additional detail on format, defaults, or edge cases, so it does not exceed the schema baseline.

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 a specific action ('Get cross-channel customer journey data') on a specific resource ('for a campaign'), with an illustrative flow (DOOH -> mobile -> web -> store). It also distinguishes itself from sibling tools by mentioning Sankey flow and cross-channel journey, which is unique among the listed get_* tools.

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 'WHEN TO USE' section explicitly lists three scenarios where this tool is appropriate, such as visualizing customer journeys and building Sankey diagrams. However, it does not explicitly state when not to use it or point to alternative sibling tools, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.3/5.0
Disambiguation2/5

There are exact duplicates (get_task_status/tasks_get, list_tasks/tasks_list) and several overlapping analytics, attribution, and semantic search clusters (get_attention_metrics vs get_creative_attention vs get_social_attention; find_similar_moments vs semantic_search_observations; get_campaign_attribution vs get_multi_touch_attribution vs get_roas). Detailed descriptions help, but with 83 tools an agent will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a snake_case verb_noun pattern (list_devices, create_campaign, delete_webhook), but there are notable inconsistencies: list_* and get_* are used interchangeably for list operations, attention tools mix conventions (get_attention_metrics vs get_creative_attention vs get_social_attention), and the legacy tasks_get/tasks_list names break the established get_task_status/list_tasks pattern.

Tool Count1/5

83 tools is an extreme count for a single MCP server, spanning device management, sensing, campaigns, media buys, attribution, webhooks, billing, API discovery, and AdCP protocol concerns. This is a broad API surface dump rather than a focused tool set, and it would be far better split into several coherent servers.

Completeness2/5

Despite the enormous surface, core campaign lifecycle is incomplete: create_campaign explicitly tells the agent to use update_campaign to activate a campaign, but no update_campaign tool exists, and there are no list/delete campaign tools. Significant capabilities exist for analytics, attribution, and webhooks, but the primary advertising workflow has a dead end.

Resources