update_brand
Replace an existing brand with new values.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Brand display name | |
| brand_id | Yes | The brand ID to update | |
| settings | No | Brand settings (colors, email, inapp) | |
| snippets | No | Brand snippets |
Replace an existing brand with new values.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Brand display name | |
| brand_id | Yes | The brand ID to update | |
| settings | No | Brand settings (colors, email, inapp) | |
| snippets | No | Brand snippets |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a non-read-only, idempotent, non-destructive write operation. The description adds little beyond saying 'replace', which is ambiguous: it could mean full replacement of all fields or partial update of provided fields. It does not clarify what happens to omitted settings or snippets, leaving a meaningful behavioral gap.
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, focused sentence with no filler. It front-loads the action ('Replace') and the object ('an existing brand'). While it is terse, it is appropriately sized for the information it tries to convey, though it omits important details that would make it more useful.
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 the nested settings and snippets objects and no output schema, the description is adequate but incomplete. It doesn't explain the replace semantics for partially specified objects, how to clear a field, or what the response contains. With no alternative guidance, an agent may not know whether omitted fields are reset or preserved.
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 parameters (name, brand_id, settings, snippets) are already documented in the input schema. The description adds no additional parameter detail or usage nuance beyond the generic 'new values', so it sits at the baseline of 3 without providing extra semantic value.
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 'Replace an existing brand with new values' identifies a clear verb and resource: it modifies an existing brand. It distinguishes from creating or deleting a brand by explicitly saying 'existing', even though it does not name sibling tools. 'Replace' is slightly ambiguous relative to the tool name 'update_brand', so it loses a point.
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 use case is implied by 'existing brand' — an agent can infer this is for updating a brand that already exists rather than creating a new one. However, it does not explicitly mention alternatives like create_brand or delete_brand, nor does it state when not to use this tool. The guidance is minimal and left to inference.
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.