Generate a JWT authentication token for a user. Used for client-side SDK auth (Inbox, Preferences, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| scopes | No | Permission scopes for the token | |
| user_id | Yes | The user ID to scope the token to | |
| expires_in | No | Token expiry duration (e.g. "1h", "2 days") | 1h |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false/neutral, so the description carries the behavioral burden. It clarifies the intended use but does not disclose details like whether the token is returned directly, how it is signed, or if generation has side effects. Still, the core behavior is clear.
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 action is front-loaded and the use case adds practical context 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?
Given low parameter count, full schema coverage, and annotations, the description is mostly complete for selection and invocation. The main gap is the absence of an output schema and no description of what the tool returns, but the name and action make the result reasonably inferable.
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?
All three parameters have schema descriptions, so schema coverage is 100%. The description adds no extra parameter-level meaning beyond naming the user and the client-side SDK context.
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 a specific verb and resource: 'Generate a JWT authentication token for a user.' The use case ('client-side SDK auth') further disambiguates it from the many user/token-related sibling tools.
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?
Provides a clear context for when to use this tool: client-side SDK auth for Inbox, Preferences, etc. It does not explicitly mention alternatives or exclusions, but no sibling tool performs JWT generation.
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.
