Update a user's preference for a specific subscription topic (opt in, opt out, or set channel preferences).
| Name | Required | Description | Default |
|---|---|---|---|
| status | Yes | Preference status | |
| user_id | Yes | The user ID | |
| topic_id | Yes | The subscription topic ID | |
| custom_routing | No | Custom channel routing order | |
| has_custom_routing | No | Whether custom channel routing is set |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false, and the description is consistent with them. The description adds value by specifying the behavioral modes (opt in, opt out, or channel preferences) beyond the generic word 'update.'
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 a single front-loaded sentence that names the action and resource before the parenthetical detail. It contains no filler, repetition, or unnecessary elaboration.
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 five-parameter mutation with complete schema documentation and safety annotations, the description is minimally adequate. However, it does not explain how to express the REQUIRED status or how the custom-routing fields work together, leaving the agent to infer those semantics from bare schema descriptions.
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%, so the baseline applies and the schema already documents all five parameters. The description maps loosely to status and custom-routing parameters, but it does not explain the relationship between custom_routing and has_custom_routing, and it omits the REQUIRED status value from the enum.
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 uses a specific verb and resource: 'Update a user's preference for a specific subscription topic,' and the parenthetical adds concrete action modes. It is clear, but it does not explicitly distinguish itself from sibling tools such as bulk_update_user_preferences or replace_preference_topic.
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 singular 'a user' and 'a specific subscription topic' imply this is for single-user, single-topic updates rather than bulk operations. However, there is no explicit guidance about when to prefer this tool over bulk_update_user_preferences, bulk_replace_user_preferences, or other preference-related siblings.
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.
