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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description goes well beyond them: it discloses model-selection mechanics (holdout backtest, keep the best model), the interval levels, the auxiliary outputs (confidence label, historical and forecast growth, plan-vs-range check, industry gap), and the execution context ('Runs on Conecto's analysis service. Free.'). It stops short of stating runtime cost, limits on series length, or failure modes.

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 core capability and the interval levels are front-loaded, and the trailing 'Runs on Conecto's analysis service. Free.' is short and useful. The middle sentence is dense with methodology (drift, ETS, Theta, holdout) that could be trimmed, but no sentence is pure filler.

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?

There is no output schema, and the description does the job of describing what comes back (confidence label, growth rates, plan check, industry gap), which is exactly what an agent needs for a nested, complex input tool. The main omissions are the meaning of 'horizon' and the frequency option, which an agent must infer from the schema alone.

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?

Top-level schema coverage is 0% — neither 'series' nor 'horizon' has a schema description. The description partially compensates: 'up to ten series' maps to the array max, and it explains that plan values are 'checked against the range' and industry growth is compared with the forecast, matching those nested fields. However, 'horizon' (default 3, max 36) and the year/quarter/month frequency choice are never explained anywhere.

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+resource ('Model forecasts ... for up to ten series') and names the input domains (revenue, EBITDA, monthly sales) plus the method family (drift on the logarithm, ETS, Theta). It is distinguishable from valuation_dcf or valuation_multiples by its forecasting framing, but it never explicitly contrasts itself with those siblings.

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?

Use is implied by the enumerated example series and the 80%/95% interval framing, so an agent can infer 'use this to project financials forward'. There is no explicit when-to-use / when-not statement and no pointer to alternatives such as valuation_dcf or valuation_benchmark for valuation rather than projection.

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