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

Annotations already declare readOnly, idempotent and non-destructive, so the safety profile is covered. The description adds substantive context beyond them: daily closing prices adjusted for splits and reinvested dividends, US-dollar denomination, skipped periods surfaced with a reason, and an explicit 'not a prediction' caveat. It stops short of stating rate limits or latency, which keeps it at a 4.

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?

Front-loaded with the core operation, then usage routing, then limits. The long enumeration of periods is justified because the underlying enum values are opaque, but the single dense paragraph could be broken up and a few clauses ('Each row gives lump sum and monthly investing results...') lean toward return-format detail that the output schema already covers.

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 4-parameter read tool with an output schema, the description covers what an agent needs: scope, period definitions, ticker universe expectations, currency, skip behavior, and an explicit not-a-prediction boundary. Return-shape details are present but non-essential, and nothing material is missing.

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%, so the baseline is 3. The description earns above baseline by decoding the cryptic enum labels into real semantics, mapping dotcom_peak, covid_low, low_2022 etc. to actual dates and explaining that they are S&P 500 closing highs and lows, plus clarifying that event dates are index-level while the ticker drives the result.

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?

States a specific verb and resource: what a fixed amount in a named US stock or index ETF became across defined reference periods ending today or on as_of_date. It explicitly names the sibling it is not (smartfin_compare_investment_strategies) and enumerates the exact period set, so an agent can distinguish it without opening a schema.

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?

Gives positive triggers ('how a stock did over several time frames', or naming a moment like 'from the COVID low') and an explicit exclusion with the correct alternative for custom start months. Nothing about when to reach for this tool is left to inference.

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