Create a new bulk job for sending messages to multiple recipients. Workflow: create_bulk_job → add_bulk_users → run_bulk_job.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | Bulk message definition with event/template and content |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, idempotentHint=false, destructiveHint=false, but carry limited detail. The description adds the multi-step workflow context, implying the created job is not yet ready to send until users are added and run. However, it doesn't disclose behaviors like persistence, auth requirements, or side effects beyond creating a job. Without additional context, this is adequate but not rich.
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 two sentences with no fluff. It front-loads the primary purpose and immediately follows with the workflow, which is essential context. Every sentence earns its place, making it highly concise and well-structured.
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?
For a creation tool with one parameter and no output schema, the description is fairly complete. It explains the tool's role in the overall process via the workflow, which is crucial for an agent. However, it doesn't mention what the response looks like (e.g., job ID), which agents might need for subsequent steps. The open-ended message structure is also not detailed, but this is partially a schema issue. Overall, it's sufficient for basic usage.
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?
The single parameter 'message' has a schema description: 'Bulk message definition with event/template and content.' Schema description coverage is 100%, so the schema already documents the parameter. The tool description adds little beyond this—only the workflow context. The description of 'message' is vague (additionalProperties open), so no extra clarity is provided. Baseline 3 is appropriate since the schema carries the burden.
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 tool's purpose: 'Create a new bulk job for sending messages to multiple recipients.' It uses a specific verb (create) and resource (bulk job), and the mention of sending messages distinguishes it from sibling tools that add users or run the job. The purpose is unambiguous and distinct from other bulk-related tools like add_bulk_users and run_bulk_job.
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 an explicit workflow: 'create_bulk_job → add_bulk_users → run_bulk_job.' This tells an agent exactly when to call this tool (as the first step in a multi-step bulk-sending process) and gives context for how it fits with siblings. It doesn't explicitly state alternatives to avoid, but the workflow sequence is clear and actionable.
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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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.
