forecast_asset_monte_carlo

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

With no annotations provided, the description carries the full burden, and it delivers thoroughly. It discloses the data source ('Downloads max adjusted daily closes'), the exact model ('EGARCH(1,1) with leverage (o=1) and skewed-t innovations'), and the simulation step ('simulates n_paths paths'). This gives the agent a clear behavioral model of what happens when invoked.

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 compact and front-loaded, with each sentence serving a purpose: purpose, when-to-use, model details, sibling routing, and parameter explanation. No filler or repetition of structured schema fields.

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 an output schema exists, return-value details need not be in the description. For a two-parameter tool, the description fully covers selection criteria, invocation parameters, model behavior, and alternative routing. There is no missing information an agent would need to call it correctly.

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 description coverage is 0%, so the description must compensate. The Args section adds meaningful detail: ticker examples ('SPY, AAPL') and n_paths constraints ('default 5000, minimum 100'). The default is redundant with the schema, but the minimum and ticker examples are new and useful.

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 opens with a specific verb-object statement: 'Run a forward Monte Carlo forecast of an asset's future price distribution.' It further enumerates concrete outputs (percentiles, volatility, drawdown, loss/gain probabilities) and explicitly contrasts with the sibling inspect_asset_model by noting diagnostics vs. simulation.

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?

It gives direct when-to-use guidance: 'Use this when the user wants scenario ranges, risk, or path statistics.' It also names the alternative with an explicit condition: 'Prefer inspect_asset_model first only when you need fit/data diagnostics without simulating paths.' This leaves no ambiguity about tool selection.

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