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Trillboards DOOH Advertising

device_heartbeat

Send a heartbeat signal from a device to report its status.

WHEN TO USE:

  • Regular device health monitoring (every 30-60 seconds)

  • Reporting current playback status

  • Reporting errors or issues

RETURNS:

  • success: Boolean indicating success

  • device_status: Current device status in system

  • next_heartbeat_seconds: Recommended interval for next heartbeat

EXAMPLE: User: "Send heartbeat for device P_abc123" device_heartbeat({ fingerprint: "P_abc123", status: "playing", current_ad_id: "507f1f77bcf86cd799439011", uptime_seconds: 3600 })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoCurrent device status
fingerprintYesDevice fingerprint (e.g., "P_abc123")
current_ad_idNoCurrently playing ad ID (if status is "playing")
error_messageNoError message (if status is "error")
uptime_secondsNoDevice uptime in seconds

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It states the action, lists return parameters (success, device_status, next_heartbeat_seconds), and provides a concrete example. However, it does not address idempotency, prerequisites, or error handling, leaving some behavioral uncertainty.

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 efficiently structured with clear sections (WHEN TO USE, RETURNS, EXAMPLE) and a front-loaded purpose. Every section adds value, and the example is instructive without being redundant with the schema.

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?

The description compensates for the lack of an output schema by explicitly listing return values and provides context on cadence and example usage. However, it omits potential prerequisites (e.g., device registration) or error conditions, making it slightly incomplete for a production context.

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 provides complete descriptions and an enum for status, so the description adds little beyond an illustrative example. The example demonstrates realistic parameter usage but does not introduce new semantic information; the schema already does the heavy lifting.

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 'Send a heartbeat signal from a device to report its status,' providing a specific verb and resource. It clearly distinguishes from sibling tools like register_device and get_device by framing it as a status-reporting action, and the WHEN TO USE section reinforces this purpose.

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 applicable contexts and recommends a cadence of every 30-60 seconds. While it does not name alternatives or exclusions, the guidance is clear and specific enough to direct appropriate use.

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

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.

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