generate_stock_research_report

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. However, it does not mention whether the report generation has side effects, requires authentication, has rate limits, or is read-only. It only describes the return format and what data is synthesized, but not behavioral traits beyond the action of generating.

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: a clear first sentence stating purpose, followed by a sentence on what the report synthesizes, then explicit usage guidance, and a parameter section. Every sentence adds value without redundancy. It is appropriately concise for a simple tool.

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?

For a tool with one parameter and no output schema, the description covers purpose, usage, parameter semantics, and return format. It does not address error handling or invalid inputs, but given the low complexity, this is acceptable. Differentiation from more siblings could be better, but the most relevant sibling (analyze_stock) is handled.

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 only parameter 'symbol' is described as 'Exchange ticker in uppercase, e.g. NVDA, TSLA, SPY'. This adds meaning beyond the schema (which only has type string and title) by specifying format and providing examples. Since schema description coverage is 0%, the description compensates well.

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 that the tool generates a structured institutional research report for a stock. It uses specific verb 'generate' and resource 'research report', and distinguishes from sibling tools like analyze_stock by noting that this returns a human-readable narrative rather than structured JSON.

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?

Explicitly provides when to use this tool (user asks for a report/write-up, needs pre-formatted narrative, document for distribution) and when to prefer analyze_stock (when needing structured JSON for programmatic use). This directly helps an AI agent decide between siblings.

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