Retrieve the final OutcomeReceipt for a completed operation.
WHEN TO USE: Use after get_status returns success/failure/partial to retrieve the full result with cost and reason codes. WHEN NOT TO USE: Do not use for operations still in pending/executing state — use get_status first. COST: free - no key required LATENCY: ~50ms
| Name | Required | Description | Default |
|---|---|---|---|
| operation_id | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it read-only and idempotent; the description adds valuable context: it requires a completed operation, returns the final receipt with cost and reason codes, is free, and has ~50ms latency. This goes well beyond the structured 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?
Every sentence earns its place: core action, use conditions, non-use conditions, cost, and latency. The WHEN TO USE/NOT format makes it skimmable and decision-ready without padding.
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 single-parameter read-only tool with rich annotations, the description covers the precondition, the sibling workflow, operational characteristics, and the content of the result. Nothing essential is missing for an agent to select and invoke it correctly.
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?
Although the schema provides zero description coverage for operation_id, the tool description supplies the meaning implicitly: it is the ID of a completed operation, and its value comes from the workflow after get_status. This is sufficient for a single clearly-named parameter, though explicit format/source details would make it stronger.
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 specific verb ('Retrieve') and resource ('final OutcomeReceipt for a completed operation'), which clearly distinguishes it from get_status and other siblings. The description also enumerates what the result contains: cost and reason codes.
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 says WHEN TO USE after get_status returns success/failure/partial, and WHEN NOT TO USE for pending/executing operations, naming get_status as the alternative. This gives an agent actionable routing logic with no ambiguity.
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.
Each tool maps to a distinct stage or concern: link preflight vs import, business discovery vs verification, scheduling, async status/outcome, cost preview, and health. The closest pair (check_booking_link and import_booking_url) is explicitly differentiated as a free guard vs actual registration.
Nearly all tools follow a consistent verb_noun snake_case pattern such as find_business, verify_business, schedule_appointment, and get_status. The only real deviation is self_test, which is a standard health-check name but not verb_noun.
Nine tools is well-scoped for an appointment-booking service that also needs async operation tracking, cost estimation, and health checks. Each tool has a clear role and none feel redundant or tacked on.
The toolset covers the main lifecycle: find or import an SMB, verify it, schedule/cancel/reschedule, poll status, retrieve outcomes, and preview costs. Minor gaps exist—send_message and capture_lead are referenced as downstream operations but not exposed, and there is no direct tool for listing supported platforms.