get_orderFetch full order detail in the selected workspace by externalId, including line items, payments, shipments and returns. Use list_orders first when you only know the customer or date.
| Name | Required | Description | Default |
|---|---|---|---|
| externalId | Yes | The order externalId returned by list_orders. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds behavioral context by listing what the order detail includes (line items, payments, shipments, returns) and scoping to the 'selected workspace'. This is useful beyond the annotations, though it doesn't describe response formatting or pagination.
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 sentences, front-loaded with the primary action and scope, followed by complementary inclusion details and usage note. Every word earns its place with zero redundancy.
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 single-parameter read tool with no output schema, the description fully equips the agent: what it does, what's included, when to use an alternative, and how to obtain the parameter. No missing context.
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 covers the only parameter (externalId) completely with 'The order externalId returned by list_orders.' The tool description repeats 'by externalId' without adding new meaning, so baseline 3 for high schema coverage is appropriate.
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 'Fetch full order detail in the selected workspace by externalId' with a specific verb (fetch), resource (order detail), and scope (workspace + externalId). It also enumerates included components (line items, payments, shipments, returns), making it distinct from sibling list/get tools.
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?
Explicit guidance is given: 'Use list_orders first when you only know the customer or date.' This directly contrasts with alternatives and informs when to use this tool versus list_orders. The schema description reinforces that externalId comes from list_orders, creating a clear workflow.
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 generally separated by entity and action, with helpful cross-references such as get_marketplace vs list_channel_products vs check_channel_readiness. The main soft spots are update_product vs adjust_stock for stock changes and the many list_/search_/get_ triplets, but descriptions mostly make the boundaries clear.
All tools follow a consistent lowercase snake_case verb_noun pattern: create_*, get_*, list_*, search_*, update_*, transition_deal, configure_pipeline, and so on. Despite the large count, the naming is highly predictable.
52 tools is an extreme surface for an agent to reason over, even though the underlying domain is broad. The set could be consolidated substantially without losing core functionality.
Most core lifecycle workflows are covered across leads, contacts, companies, products, orders, and activities. However, there are notable gaps: deals cannot be updated except by stage transition, activities cannot be edited or rescheduled, and there are no delete operations at all, only status-based archiving.