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

Annotations indicate read-only and closed-world behavior. The description adds value by explaining that the tool orchestrates internal searches and returns a synthesized narrative with source citations. It also mentions cost differences between model options. While transparent, it lacks explicit details about potential time or scope limits.

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 reasonably concise at about six sentences, with the core purpose front-loaded. Each sentence adds value, and there is no redundancy. Minor improvements could tighten the phrasing, but overall structure is effective.

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 presence of an output schema (covering return value details), the description provides adequate context: scope (Nordic financial data), data sources, and citation behavior. Some might expect explicit mention of supported company formats or geographic limitations, but overall completeness is strong.

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 100%, and the schema already provides detailed descriptions for all parameters (including examples and cost info). The tool description's parameter section merely repeats the schema without adding new semantic value, meeting the baseline but not exceeding it.

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 explicitly states it performs 'AI-powered company analysis using semantic search over Nordic financial data' and distinguishes itself from sibling tools by emphasizing it returns a synthesized narrative answer with citations rather than raw data. It clearly identifies the verb (analyze/answer), resource (Nordic financial data), and scope.

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 gives explicit when-to-use guidance: 'Use this when you want a synthesized answer rather than raw search chunks.' It also provides clear alternatives: 'For raw data access, use search_filings or company_research instead.' Additionally, it directs users to an external server for full due diligence reports, covering all usage contexts.

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