get_full_stock_analysis

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds context about the scope of data fetched (multiple sources), but does not disclose additional behavioral traits such as rate limits or data freshness. The added value is moderate.

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 extremely concise: two sentences that front-load the main purpose and list components. Every sentence adds value without redundancy.

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 simple two-parameter schema and rich annotations, the description is largely complete. It could briefly mention the output structure since no output schema is provided, but the listed components give sufficient context for an AI agent to understand the tool's coverage.

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 coverage is 100% with both parameters already documented. The description provides no additional parameter details beyond the schema. Baseline score of 3 is appropriate given high schema coverage.

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 it fetches comprehensive stock analysis data including quotes, technical indicators, institutional investors, monthly revenue, and news sentiment. It distinguishes from sibling tools by explicitly listing the combined data sources and targeting 'complete analysis' queries.

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 mentions suitability for 'help me fully analyze XXXX' type questions, providing clear context for when to use this tool. However, it does not explicitly state when not to use it or name alternative tools for more specific queries.

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