Create a new user profile or merge supplied values into an existing profile (POST). Existing fields not included are preserved.
| Name | Required | Description | Default |
|---|---|---|---|
| profile | No | Profile data to create or merge (e.g. { email: "...", phone_number: "..." }) | |
| user_id | Yes | The user ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a mutating, idempotent, non-destructive operation. The description adds valuable behavioral detail beyond those flags by explaining that omitted fields are preserved, which clarifies the upsert semantics. It does not disclose response behavior or error conditions, but the annotations cover the core safety profile.
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 sentence conveys the core action, the update behavior, and the crucial preservation guarantee. Every clause earns its place, with no filler or repetition of schema details.
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 only two parameters and a clear behavior, and the description plus schema cover what an agent needs to invoke it correctly. There is no output schema, so return-value details are absent, but that gap is not critical for an upsert operation whose inputs and semantics are well specified.
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 schema already documents user_id and profile with an example. The description's phrase 'supplied values' loosely maps to the profile parameter but adds little new semantic detail beyond what the schema provides. Baseline 3 is appropriate given full schema 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 clearly identifies the action (create or merge), the resource (user profile), and the critical merge behavior ('Existing fields not included are preserved'). This also distinguishes it from sibling tools like replace_profile and patch_profile without naming them, because preservation semantics are explicit.
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 clear context for when the tool is appropriate: when creating a new profile or updating an existing one with a partial set of values. However, it does not explicitly state when to use an alternative (e.g., patch_profile or replace_profile) or list exclusions, so it stops short of full guidance.
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.
