cancel_message
Cancel a message that is currently being delivered. Returns the message details with updated status.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | Yes | The message ID to cancel |
Cancel a message that is currently being delivered. Returns the message details with updated status.
| Name | Required | Description | Default |
|---|---|---|---|
| message_id | Yes | The message ID to cancel |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal destructive and idempotent behavior. The description adds meaningful context by specifying the in-delivery precondition and stating that the return value contains the message details with updated status. This goes beyond what annotations and schema provide, with no contradiction.
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?
Two short sentences with no filler. The core action and precondition are front-loaded, and the return behavior is stated efficiently in the second sentence.
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 single-parameter destructive action, the description covers the action, the valid precondition, and the return value. Annotations cover idempotency and destructiveness, so nothing essential is missing for an agent to invoke it correctly.
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?
The schema describes message_id as 'The message ID to cancel' with 100% parameter coverage, so the schema already carries the meaning. The description adds no additional syntax, format, or source guidance for the parameter, which lands at the expected baseline.
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?
States an explicit action ('Cancel'), a specific resource ('a message'), and a precondition ('currently being delivered'). This clearly differentiates it from sibling tools like cancel_automation, cancel_journey, and cancel_notification_submission without needing to inspect their schemas.
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 phrase 'currently being delivered' gives a clear condition for when this tool applies, which helps an agent decide whether cancellation is appropriate. It does not explicitly name alternatives or exclusions, but the precondition is contextually strong enough for basic routing.
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.