bulk_add_user_tokens
Add multiple push/device tokens for a user in one request. Overwrites matching existing tokens.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tokens | Yes | Token records to upsert | |
| user_id | Yes | The user ID |
Add multiple push/device tokens for a user in one request. Overwrites matching existing tokens.
| Name | Required | Description | Default |
|---|---|---|---|
| tokens | Yes | Token records to upsert | |
| user_id | Yes | The user ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a write operation, so the description adds value by disclosing that matching existing tokens are overwritten rather than appended, preventing duplicate accumulation. It does not cover failure modes or what counts as a 'matching' token, but the overwrite behavior is a meaningful disclosure beyond the annotations.
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 exactly two sentences: the first delivers the primary action and scope, and the second adds the critical overwrite behavior. There is no filler or redundant restatement of the tool name.
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 bulk mutation with a nested token schema and no output schema, the description covers the core semantics but leaves gaps: it does not explain the key used to match existing tokens, how duplicates inside the same request are handled, or what response/error behavior to expect. It is serviceable for basic invocation but not fully complete.
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 input schema fully documents both parameters and nested fields like token, provider_key, expiry_date, and device metadata, so the description does not need to repeat them. The description adds only the generic framing of 'push/device tokens,' which does not elevate it beyond the schema baseline.
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 states a specific action—adding multiple push/device tokens for a user in one request—and distinguishes it from singular token tools like create_or_replace_user_push_token by emphasizing batch operation. The overwrite note further clarifies the operation's semantics.
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 implies the batch use case with 'multiple tokens in one request' and upsert behavior with 'overwrites matching existing tokens,' but it never explicitly names alternatives or states when to prefer this over a singular token tool. No exclusions or conditions are provided.
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.