Update check statuses for a notification submission.
| Name | Required | Description | Default |
|---|---|---|---|
| checks | Yes | Checks to update | |
| submission_id | Yes | The submission ID for the checks resource | |
| notification_id | Yes | The notification template ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the operation is a non-read-only, idempotent, non-destructive update, and the description adds no behavioral detail beyond the verb. It does not disclose whether existing checks are replaced, whether status transitions are validated, or what happens when the submission is already final.
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?
A single front-loaded sentence with no filler. It is concise, though the available space could have been used to add behavioral context without harming clarity.
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?
For a mutation tool with three required parameters and no output schema, the description does not explain the effect on existing checks, required lifecycle state, or what a successful update returns. It is minimal but not sufficient on its own.
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 100%, with descriptions for notification_id, submission_id, and checks, so the schema carries the parameter documentation. The description itself adds no additional parameter semantics, yielding the baseline score.
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 names a specific verb, resource, and object: 'Update check statuses for a notification submission.' This clearly distinguishes it from read-only siblings like list_notification_checks and from submission-level actions like cancel_notification_submission.
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?
No guidance is given about when to update checks versus auditing or cancelling a notification submission, and no alternative tools are named. The usage context is only implied by the resource name and sibling set.
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.
Tools are mostly organized as distinct resource/action pairs, but several clusters are easy to confuse: list subscription tools (add_subscribers_to_list vs bulk_subscribe_to_list vs subscribe_user_to_list), message vs message-content vs message-history retrieval, and the many journey/journey-template list/get tools. Detailed descriptions rescue most selections, but the sheer number of near-identical verb/resource names creates real misselection risk.
Almost all tools follow a snake_case verb_noun pattern (create_, get_, list_, replace_, send_, publish_, archive_). Minor deviations keep it from a perfect score: courier_installation_guide is noun-first, and add_bulk_users sits awkwardly next to the bulk_add_* family, but the overall convention is predictable and readable.
144 tools is an extreme working-set size for an agent to hold and choose from, far beyond the reasonable 3–15 range. Even for a broad platform like Courier, this should be split into focused sub-servers (templates, journeys, users, lists, preferences, etc.) to remain usable.
The surface is remarkably comprehensive, covering sending, templates, journeys, automations, users, tenants, lists, preferences, providers, routing, brands, audiences, translations, digests, bulk jobs, and audit events. Notable gaps exist—automation template CRUD and digest schedule management are missing—but most workflows can still be completed with workarounds.
