list_routing_strategies
List routing strategies in the workspace. Returns metadata only; use get for full details.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results per page (default 20, max 100) | |
| cursor | No | Pagination cursor |
List routing strategies in the workspace. Returns metadata only; use get for full details.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results per page (default 20, max 100) | |
| cursor | No | Pagination cursor |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds 'Returns metadata only', which clarifies response granularity, but it doesn't disclose pagination behavior, ordering, or errors. This is useful but not rich behavioral context.
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?
Two short sentences with no filler, front-loaded with the primary action. Every sentence earns its place.
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 simple read-only list with two optional, well-documented parameters, the description plus annotations provide everything needed to invoke it correctly. It also properly routes to get_routing_strategy for full details.
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% with clear descriptions for limit and cursor. The description adds no additional parameter semantics, and per baseline a 3 is appropriate when the schema already does the heavy lifting.
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?
States a concrete verb ('List'), a specific resource ('routing strategies'), and a scope ('in the workspace'). The phrase 'Returns metadata only; use get for full details' differentiates it from get_routing_strategy.
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?
Explicitly tells the agent this tool is for listing metadata and directs it to the get tool when full details are needed. This is a clear when-to-use versus alternative guidance, even though it doesn't enumerate every sibling.
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.