Skip to main content
Glama

Trillboards DOOH Advertising

by io.github.snehdhruv

register_device

Register or update a device in the partner's network.

WHEN TO USE:

  • Adding a new screen/kiosk/vending machine to the network

  • Updating device location or configuration

  • Re-registering a device after maintenance

RETURNS:

  • device_id: Your internal device ID (echoed back)

  • trillboards_device_id: Internal Trillboards device ID

  • fingerprint: Device fingerprint (e.g., "P_abc123")

  • embed_url: URL to load in the device's WebView

  • status: Device status

EXAMPLE: User: "Register a vending machine in NYC" register_device({ device_id: "vending-001-nyc", name: "NYC Office Lobby Vending", device_type: "vending_machine", location: { lat: 40.7128, lng: -74.0060, city: "New York", state: "NY", venue_type: "office" } })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoHuman-readable device name
specsNoDevice specifications
locationNoDevice location information
metadataNoAdditional custom metadata
device_idYesYour internal unique device identifier
device_typeNoType of device

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the return payload (device_id, trillboards_device_id, fingerprint, embed_url, status) and gives a concrete example. While it doesn't detail side effects or auth requirements, the upsert nature is implied by 'register or update'.

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-organized with clear sections (main purpose, WHEN TO USE, RETURNS, EXAMPLE). Each section earns its place, with no redundant content. It's appropriately sized for the tool's complexity.

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 the tool's nested objects (specs, location) and missing output schema, the description compensates by listing all return fields and showing a complete example. It doesn't cover error handling, but the essential usage context is thorough.

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%, so the baseline is 3. The description adds an example with device_id, name, device_type, and location, demonstrating real-world usage, but the schema already fully explains each parameter. No significant extra semantic info.

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 'Register or update a device in the partner's network', clearly stating the verb (register/update) and resource (device). It distinguishes from siblings like delete_device, get_device, and list_devices by covering both creation and modification scenarios.

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?

Explicit 'WHEN TO USE' section lists three concrete scenarios: adding a new screen/kiosk/vending machine, updating device info, and re-registering after maintenance. It lacks explicit when-not-to-use or alternatives, but the use cases are clear enough.

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