Skip to main content
Glama

Trillboards DOOH Advertising

by io.github.snehdhruv

get_campaign_heatmap

Get geographic exposure heatmap data for a campaign.

Returns lat/lng clusters with exposure counts and device reach, useful for visualizing where ads were shown on a map.

WHEN TO USE:

  • Visualizing campaign geographic coverage

  • Identifying hotspots of ad exposure

  • Analyzing geographic distribution of attributed foot traffic

RETURNS: Array of geographic clusters (max 500), each with:

  • lat, lng (rounded to 3 decimal places)

  • uniqueDevices, totalExposures

  • avgConfidence (match confidence score)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYesCampaign identifier

TDQS

A4/5.0
Behavior3/5

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

No annotations are present, so the description must carry the full burden. It discloses return format details, including max 500 clusters, lat/lng rounding to 3 decimals, and specific fields like uniqueDevices and avgConfidence. However, it does not explicitly state read-only behavior, permissions, or data freshness, leaving a moderate gap.

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 moderately sized but well-structured with clear sections: purpose, when-to-use, and return details. Each section earns its place, though the phrase 'exposure' repeats several times and could be tightened slightly.

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?

With only one parameter and no output schema, the description thoroughly covers return fields, limits, and rounding behavior. The use cases add practical context. For a simple data retrieval tool, this is complete and self-sufficient.

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 provides 100% coverage for the single campaign_id parameter with a description ('Campaign identifier'). The tool description adds no additional parameter semantics, so the baseline of 3 applies.

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 opens with 'Get geographic exposure heatmap data for a campaign', using a specific verb and resource that clearly differentiates it from sibling tools like get_campaign_performance or get_analytics. The map visualization context further clarifies intent.

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?

A dedicated 'WHEN TO USE' section provides concrete use cases such as 'Visualizing campaign geographic coverage' and 'Identifying hotspots of ad exposure'. It does not explicitly mention when not to use or name alternatives, but the context is clear enough for a straightforward GET tool.

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

All Trillboards DOOH Advertising toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

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