alpaca-mcp-server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds valuable behavioral context beyond annotations. Annotations indicate destructiveHint=true and idempotentHint=false, but the description clarifies idempotency via client_order_id: 'If the request times out, you can safely retry with the same value — the API will reject duplicates.' It also notes mutual exclusivity rules (qty vs. notional) and order-type dependencies, enhancing transparency without contradicting 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 well-structured with a brief purpose statement followed by a parameter list. Each parameter explanation is concise and informative. However, the initial purpose line is somewhat redundant with the title, and some sentences could be tighter (e.g., the client_order_id explanation is slightly verbose), keeping it from a perfect score.

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 complexity (9 parameters, destructive operation) and 0% schema coverage, the description is highly complete. It covers all parameters, behavioral nuances, and constraints. With an output schema present, it appropriately omits return value details. The annotations provide safety hints, and the description fills in critical gaps like idempotency and order logic.

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?

With 0% schema description coverage, the description fully compensates by explaining all 9 parameters in detail. It clarifies meanings (e.g., 'Crypto pair'), constraints (e.g., 'Mutually exclusive with qty'), dependencies (e.g., 'Required for limit and stop_limit orders'), and usage notes (e.g., 'Unique idempotency key'). This adds significant semantic value beyond the bare schema.

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's purpose: 'Place a cryptocurrency order.' It specifies the verb ('place') and resource ('cryptocurrency order'), distinguishing it from sibling tools like 'place_stock_order' and 'place_option_order' which handle different asset types. This makes the purpose specific and differentiated from alternatives.

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 provides clear context for usage through parameter explanations (e.g., 'Only valid for market orders' for notional, 'Crypto does not support "day" or "fok"' for time_in_force). However, it does not explicitly state when to use this tool versus alternatives like 'place_stock_order' or general guidance on order placement scenarios, which prevents a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.