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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds substantial operational context: cost ('free - no key required'), latency (~50ms), and a state precondition (do not call before completion). No contradiction with annotations. The extra details go well beyond what the annotations already provide.
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 compact and well-organized: a one-sentence purpose followed by labeled WHEN TO USE, WHEN NOT TO USE, COST, and LATENCY sections. Every sentence earns its place and the main purpose is front-loaded. Minor mojibake in the dash appears to be an encoding artifact rather than a content flaw.
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 tool with no output schema, the description covers purpose, prerequisite state, cost, latency, and hints at return contents ('cost and reason codes'). It does not describe error cases or the exact response shape, but those gaps are minor given the tool's simplicity and annotations.
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 schema has one required parameter, operation_id, with 0% schema description coverage. The description implies that operation_id identifies the operation whose outcome is being retrieved and that it should come from a completed operation, but it never explicitly defines operation_id or its source. It partially compensates for the lack of schema descriptions but could be more direct.
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 verb ('Retrieve'), a specific resource ('final OutcomeReceipt'), and a scope ('completed operation'), making the tool's function immediately clear. It also implicitly distinguishes itself from get_status by positioning this as the terminal retrieval step. No tautology or ambiguity.
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?
Contains explicit WHEN TO USE and WHEN NOT TO USE sections. It names get_status as the prerequisite and alternative, specifies that the tool should only be called after get_status returns success/failure/partial, and warns against calling while operations are pending/executing. This is ideal routing guidance.
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.
Most tools have clearly distinct roles: compliance preflight, messaging, transactional sends, directory lookup, conversation/status/outcome retrieval, cost preview, and health check. The main ambiguity is between send_message and send_transactional_confirmation, both of which can handle booking confirmations and transactional message types, though the descriptions do provide guardrails.
All tool names follow a consistent snake_case verb_noun pattern: check_compliance, find_business, get_conversation, get_outcome, get_status, preview_cost, send_message, verify_business. Even longer names like send_transactional_confirmation stay within the same convention. No mixed casing or inconsistent verb styles.
10 tools is well-scoped for a business messaging platform. Each tool covers a distinct aspect: search/verify businesses, check compliance, send messages, preview costs, and inspect async results. The count is neither bloated nor thin for the stated purpose.
The core workflows are covered: find/verify a business, check compliance, send messages, retrieve conversations, and get operation outcomes. Minor gaps exist, such as no explicit tool for managing consent records and no webhook configuration tool, but agents can still complete primary messaging tasks without dead ends.