get_transaction_receiptUse this for receipt logs, status and gas usage of a transaction. Prefers Explorer decoded receipt data.
| Name | Required | Description | Default |
|---|---|---|---|
| txHash | Yes | 0x-prefixed transaction hash to inspect or resolve. |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Structured result data returned by the XGR MCP gateway. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds 'Prefers Explorer decoded receipt data,' which gives context about data sourcing but does not detail behavior when Explorer data is unavailable. This adds marginal value over 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 two short, direct sentences with no extraneous words. It is front-loaded with the main purpose, achieving high efficiency.
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?
Given the simple single-parameter tool with full schema coverage and an output schema present, the description sufficiently covers the core functionality. It could mention the output format briefly, but the output schema handles that. Complete for the tool's complexity.
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 single parameter txHash has 100% schema coverage with a clear description. The tool description does not add any additional parameter semantics beyond what the schema provides, so the baseline score of 3 applies.
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 the tool retrieves receipt logs, status, and gas usage for a transaction. The purpose is specific and actionable. However, it does not explicitly distinguish from sibling tools like get_session_receipt_logs, relying on the tool name for differentiation.
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 usage for receipt data but does not specify when to use this tool versus alternatives. There is no mention of when-not-to-use or alternative tools, providing only implied 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.
There are many overlapping session-listing tools (list_xdala_sessions, get_recent_xdala_sessions, find_latest_xdala_session, list_xdala_session_ids, get_latest_session_payload) and duplicate validation tools (validate_xdala_bundle is an alias for validate_xgr_multibundle). Descriptions help but boundaries are still unclear.
The verb_noun snake_case pattern is consistent across nearly all tools (get_, list_, create_, cancel_, validate_). Minor inconsistencies include the alias validate_xdala_bundle and interchangeable verbs like get_ vs read_ vs resolve_ for similar read operations.
With 95 tools, this is far beyond the 25+ threshold for 'too many'. While the domain is broad, the sheer number makes the tool surface unwieldy and difficult for an agent to navigate.
The tool set covers a wide range of operations: handoffs, session queries, transaction exploration, contract reads, validation, gas requests, and purchases. Minor gaps exist (e.g., no direct workflow editing tools), but overall the surface is remarkably complete.