get_xgr_purchase_optionsCall this first for every XGR purchase. Read live price, stock and payment assets; use payment_assets[].key exactly as payment_asset and inspect requires_sender_wallet before creating an order.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description's 'Read live price' aligns with them. It adds valuable behavioral details beyond annotations: instructing to inspect requires_sender_wallet and to use payment_assets[].key exactly, which are key behavioral constraints for correctly invoking subsequent order creation. No contradiction detected.
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, both dense and meaningful. The first sentence front-loads the primary purpose and ordering. The second provides precise field-level instructions. No fluff, no repetition of schema or annotations.
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 read-only, zero-parameter tool with a rich output schema, the description covers the essential workflow context: when to call, what data to expect, and how to use it correctly. It gives enough to distinguish from siblings like quote_xgr_purchase and create_xgr_purchase_order. The existence of an output schema reduces the need to document return values.
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?
Tool has zero parameters, and schema coverage is trivially 100%. Baseline for 0 params is 4. The description adds no parameter-level semantics (as there are none), but it does explain how to use the output fields (payment_assets[], requires_sender_wallet) that will feed into subsequent tool calls, which is relevant context.
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 specifies a clear action ('Read live price, stock and payment assets') with a specific resource (XGR purchase options). It distinguishes itself from sibling tools by framing itself as the mandatory first step for every XGR purchase, which differentiates it from order-creation and quotation 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?
It explicitly states when to use this tool ('Call this first for every XGR purchase') and how it fits into the workflow ('before creating an order'). It also gives direct downstream guidance ('use payment_assets[].key exactly as payment_asset'), effectively telling the agent when and how to apply the data, which is clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.