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Trillboards DOOH Advertising

get_media_buy_delivery

[AdCP Media Buy] Get delivery/performance report for a media buy.

Returns campaign performance with breakdowns by screen, venue, hour, and audience segment.

WHEN TO USE:

  • Monitoring campaign delivery in real-time

  • Getting performance breakdowns for optimization

  • Reporting on campaign results

RETURNS:

  • delivery: impressions, spend, avg_cpm, unique_screens, fill_rate

  • breakdowns: by_screen, by_venue, by_hour (top performers)

EXAMPLE: get_media_buy_delivery({ media_buy_id: "mbuy_abc123" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dimensionsNoReporting dimensions to include. Only "screen" is supported; anything else is returned in dimensions_unsupported rather than silently dropped.
breakdown_byNoDimensions to break down by (legacy, prefer dimensions). Same single supported value.
media_buy_idYesMedia buy ID

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the behavioral burden. It lists return metrics and breakdowns, but it claims breakdowns by venue, hour, and audience segment while the schema says only 'screen' is supported, and it omits the dimensions_unsupported behavior. This is misleading and incomplete.

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 well organized with WHEN TO USE, RETURNS, and EXAMPLE sections and is front-loaded with the main purpose. There is minor redundancy between the opening line and RETURNS, but the structure helps an agent scan it.

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?

No output schema exists, so the description must explain return behavior, which it does only partially. The omission of the single-supported-dimension constraint and the dimensions_unsupported response is a significant gap that could cause an agent to request unsupported breakdowns and misread the results.

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 coverage is 100%, so the schema already documents all parameters clearly, including the critical 'only screen is supported' note. The description's example shows media_buy_id usage and its return summary hints at what dimensions produce, but it does not add meaningful parameter semantics beyond the schema.

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?

States a specific action and resource: 'Get delivery/performance report for a media buy.' The resource (media buy) distinguishes it from many sibling get_* tools, though it does not explicitly name a sibling or alternative.

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?

Provides a WHEN TO USE section with concrete scenarios: real-time monitoring, performance breakdowns for optimization, and reporting. It does not spell out when to prefer a sibling tool like get_campaign_performance or get_analytics, so no explicit exclusion is given.

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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