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create_brand

Create a new brand. The API requires settings — omitting it returns a 400. If you do not have specific brand colors, omit settings and a safe default will be used automatically (black primary, white secondary). Example: { name: "Acme", settings: { colors: { primary: "#1a73e8", secondary: "#ffffff" } } }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoOptional brand ID; auto-generated if omitted
nameYesBrand display name
settingsNoBrand appearance settings. If omitted, defaults to { colors: { primary: "#000000", secondary: "#ffffff" } }.
snippetsNoBrand snippets

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses a 400-on-omitted-settings behavior and a safe default, but the two statements contradict each other: it first says omitting settings returns 400, then says omitting settings uses a safe default. The schema already documents the default, and the annotations carry little behavioral content, so the contradictory claims reduce transparency rather than add it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately short at three sentences with an example, and it front-loads the core purpose. However, the self-contradictory middle sentence harms clarity, keeping this from a higher score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With nested settings/colors objects and no output schema, the description needed to clearly explain when settings are required and what happens if omitted. Instead it gives conflicting answers, so an agent cannot reliably decide whether to send settings. The schema fills some gaps, but the tool-level description is not complete enough on its own.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The example adds a concrete structure for settings.colors, and the second sentence offers a heuristic for omitting settings, but the contradictory 'requires settings' statement undercuts that guidance and prevents a higher score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening phrase 'Create a new brand' clearly states the verb and resource, and 'new' distinguishes this from update_brand, delete_brand, get_brand, and list_brands. Even without naming siblings, the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool—creating a new brand—and offers guidance about when to omit settings (when no specific brand colors are available). However, it never explicitly states the alternative for updating an existing brand or gives a clear when-not-to-use condition.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness4/5

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.