Avanza MCP Server

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

No annotations are provided, so the description carries the full burden. It describes what data is returned (financial ratios grouped by time periods) but doesn't disclose behavioral traits like rate limits, authentication needs, error conditions, or whether this is a read-only operation. The description adds value by outlining the structure of returned data but lacks operational context.

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 appropriately sized and front-loaded with the core purpose. Every sentence adds value: the first states the purpose, the second details the data structure, the third provides usage guidance, and the rest document parameters and examples. Minor redundancy exists in listing return data both in bullet points and the 'Returns' section.

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 (financial analysis with multiple data groupings), no annotations, and an output schema exists, the description is reasonably complete. It explains the purpose, usage prerequisites, parameter meaning, and return structure. However, it lacks behavioral context (rate limits, errors) that would be helpful despite the output schema.

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?

Schema description coverage is 0%, but the description compensates well. It explains that instrument_id is 'Avanza instrument ID from search results' and provides an example ('Volvo B (ID from search): >>> get_stock_analysis(instrument_id="5479")'). This adds crucial semantic meaning beyond the bare schema, though it doesn't detail format constraints or validation rules.

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: 'Get detailed stock analysis with key financial ratios.' It specifies the verb ('Get') and resource ('stock analysis'), and distinguishes it from siblings like get_stock_info or get_company_financials by focusing on financial ratios rather than general information or raw financials.

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 explicitly states when to use this tool: 'Use search_instruments() first to find the instrument_id for a stock.' It names the specific alternative tool (search_instruments) that must be used beforehand, providing clear prerequisites and distinguishing it from other stock-related tools.

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