alpaca-mcp-server

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

Annotations provide readOnlyHint=true and openWorldHint=true, indicating safe read operations with open-ended data. The description adds valuable behavioral context beyond this: it explains how omitted parameters trigger automatic computations (e.g., 'start' defaults to now minus lookback), specifies data limits and ranges ('1–10000'), and describes sorting options. This enhances 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 and front-loaded with the core purpose, followed by a clear 'Args:' section detailing each parameter. Every sentence earns its place by providing essential information without redundancy, making it efficient and easy to parse.

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 tool's complexity (8 parameters, 0% schema coverage) and the presence of annotations and an output schema, the description is complete. It thoroughly explains parameter usage and behaviors, and since an output schema exists, it appropriately omits return value details, focusing on what the agent needs to invoke the tool 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?

With 0% schema description coverage, the description fully compensates by providing detailed semantics for all 8 parameters. It explains each parameter's purpose, format (e.g., 'comma-separated crypto pairs', 'RFC 3339'), default values, interactions (e.g., 'start' omission triggers lookback), and constraints (e.g., 'limit' range). This adds significant 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 with a specific verb ('retrieve') and resource ('historical trade data for one or more cryptocurrencies'), making it immediately understandable. It distinguishes itself from sibling tools like 'get_crypto_bars' or 'get_crypto_latest_trade' by focusing on historical trade data retrieval rather than bars, latest data, or other asset types.

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 the explanation of default behaviors when parameters like 'start' are omitted, and it implicitly distinguishes from alternatives by specifying it retrieves 'historical trade data' (not real-time or aggregated data). However, it does not explicitly state when NOT to use this tool or name specific alternatives among siblings.

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