Partially update a user profile via JSON Patch (RFC 6902). Use add/replace/remove operations on specific profile paths.
| Name | Required | Description | Default |
|---|---|---|---|
| patch | Yes | Array of JSON Patch operations to apply to the profile | |
| user_id | Yes | The user ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations establish that this is a non-read-only, non-idempotent write operation. The description adds meaningful behavioral context by clarifying that the update is partial and that remove operations are permitted, signaling possible field deletion beyond what the raw annotation flags convey.
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 entire description is one focused sentence: it front-loads the action, names the protocol, and states the allowed operations. There is no filler or redundant content.
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 only two documented parameters and no output schema, the description covers what the agent needs to invoke the tool correctly. A minor gap is that it does not mention whether the updated profile is returned, but this is not essential for a mutation tool with well-documented inputs.
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 coverage is 100%, so both parameters are already documented. The description adds modest value by narrowing the operation set to add/replace/remove, which differs slightly from the schema's broader enum (add, remove, replace, move, copy, test), but it does not otherwise enrich parameter meaning.
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 states the verb ('partially update'), the resource ('user profile'), and the method ('JSON Patch (RFC 6902)'). It differentiates itself from the sibling 'replace_profile' by specifying partial, path-scoped updates rather than wholesale replacement.
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 usage context is implied: use this when a partial, path-specific profile update is needed. The description also instructs which patch operations to use (add/replace/remove), but it does not explicitly name alternatives or provide when-not-to-use 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.
