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Trillboards DOOH Advertising

list_endpoints

List every registered Trillboards API operation.

WHEN TO USE:

  • First call in an agent session to learn what the API offers.

  • Filter to agent_safe=true to list only side-effect-free endpoints.

  • Narrow to a single surface (data-api, sdk-api, device-api, sensing-api, partner-api-generated, dsp-api-generated).

RETURNS:

  • operations: Array of { surface, method, path, operation_id, summary, description, agent_safe, idempotent, cost_tier, tags, doc_url, example_request }

  • total_operations: Total count.

  • surfaces: Known surface identifiers.

EXAMPLE: Agent: "What read-only endpoints can I call?" list_endpoints({ agent_safe: true })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
surfaceNoFilter to one surface (e.g. "data-api").
agent_safeNoWhen true, return only endpoints flagged agent-safe.
idempotentNoWhen true, return only endpoints flagged idempotent.

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the return structure in detail, including operations array, total_operations, and surfaces, and explains filtering behavior. It does not mention potential rate limits or auth, but for a read-only list tool, it provides substantial behavioral context.

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 into WHEN TO USE, RETURNS, and EXAMPLE sections. Every section contributes essential information: usage context, return fields, and a concrete invocation. It is appropriately sized without fluff.

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 no output schema and no annotations, the description fully compensates by declaring all return fields, explaining the surface concept, and providing a usage example. It is comprehensive enough for an agent to understand what list_endpoints does and how to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 value by explaining the practical meaning of agent_safe ('side-effect-free endpoints') and giving a concrete example with agent_safe: true, going slightly beyond the schema's terse descriptions.

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 immediately states 'List every registered Trillbirds API operation,' using a specific verb and resource. It clearly distinguishes from the sibling tool describe_endpoint by covering all operations rather than just one.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'WHEN TO USE' section explicitly says to use this as a first call in an agent session, to filter with agent_safe, and to narrow by surface. This provides concrete context and contrasts with more specific tools like describe_endpoint, even though it does not name alternatives directly.

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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