Get Analyst Estimates

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

Annotations already declare readOnlyHint=true, so the description's safety profile is covered. The description adds that it returns forward estimates but does not detail behavior on invalid tickers or rate limits. Overall adequate, but no significant extra transparency beyond the annotation.

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 consists of two concise sentences. The first sentence covers purpose and key outputs, the second provides usage context. No unnecessary words, and the most important information is front-loaded.

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 three parameters and existing output schema, the description is complete for an agent to understand the tool's purpose and when to use it. It does not need to explain return values since the output schema exists. Minor gaps (e.g., error handling) are acceptable for a simple read tool.

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%, but the description adds meaning by listing the financial metrics (EPS, revenue, EBITDA, net income) and stating support for annual/quarterly periods, which is not present in the schema descriptions. This helps an AI agent understand what values to expect.

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 retrieves forward analyst estimates (EPS, revenue, EBITDA, net income) with low/high/avg and analyst counts. It distinguishes itself from sibling tools like get_analyst_consensus or get_analyst_grades by specifying it provides detailed breakdowns per period.

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 says 'Use when analyzing forward earnings expectations or revenue forecasts,' providing clear context. It does not specify when not to use it, but the guidance is sufficient for an AI agent to identify relevant scenarios.

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