Avanza MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool returns 'First matching search hit if found, None otherwise,' which clarifies the return behavior. However, it lacks details on error handling, rate limits, authentication needs, or whether this is a read-only operation. For a lookup tool with zero annotation coverage, this leaves significant behavioral gaps.

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 sections for Args, Returns, and Examples. Every sentence adds value: the first defines the tool, the second explains the parameter source, and the rest provide implementation details. There's no wasted text, 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 low complexity (one parameter) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the purpose, parameter semantics, and return behavior, though it lacks details on errors or operational constraints. For a simple lookup tool, this is sufficient but could be enhanced with more behavioral context.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'order_book_id' is 'the unique identifier returned from search results,' providing context beyond the schema's basic string type. However, it doesn't specify format constraints (e.g., numeric string) or examples beyond one case, leaving some ambiguity. With only one parameter, this is adequate but not exhaustive.

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: 'Look up a financial instrument by its order book ID.' It specifies the verb ('look up') and resource ('financial instrument'), and distinguishes it from siblings like 'search_instruments' by focusing on ID-based lookup rather than general search. However, it doesn't explicitly contrast with 'get_orderbook' or 'get_stock_info', which might also retrieve instrument data, leaving some sibling differentiation incomplete.

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 by stating 'The order book ID is the unique identifier returned from search results,' suggesting this tool should be used after obtaining an ID from search operations. It doesn't provide explicit when-to-use vs. when-not-to-use guidance or name alternatives like 'search_instruments' for broader queries, leaving usage context somewhat inferred rather than clearly defined.

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