[AdCP Protocol] List AdCP tasks belonging to your account, newest first.
Returns query_summary (totals and a status breakdown), tasks, and
pagination. Filter by status or task type. Scoped to the calling account —
an unauthenticated call returns an empty page rather than another account's
tasks.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| context | No | ||
| filters | No | Narrow the returned tasks. | |
| pagination | No |
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 several behavioral traits: newest-first ordering, account scoping, and that unauthenticated calls return an empty page rather than another account's data. It also names the returned top-level components. This is solid for a read/list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tight and front-loaded: the purpose appears in the first sentence, followed by return value names, filtering capability, and a key scoping caveat. Every sentence contributes useful information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has nested parameters, no output schema, and no annotations, so the description must carry more weight. It provides a helpful overview of return values, filtering, and scope, but it does not explain pagination usage, the meaning of the account/context objects, or task payload structure. Gaps remain for an agent to invoke it optimally.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25%, so the description must compensate, but it only mentions 'filter by status or task type.' It adds no meaning for the account, context, or pagination parameters beyond what the schema already shows. This is insufficient given the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'List AdCP tasks belonging to your account, newest first.' It is clear about what the tool does and even adds an ordering guarantee. It does not explicitly distinguish itself from sibling tools such as tasks_list or tasks_get, so it misses the top score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context about filtering and account scoping, but gives no explicit guidance on when to use this tool versus alternatives like tasks_list, tasks_get, or get_task_status. No exclusions or selection criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.