simulate_price

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

No annotations exist, so the description fully bears the transparency burden. It explains the math, data sources, calibration steps, and fallback priors in detail. However, it does not explicitly state if the tool is purely read-only or mention potential side effects, but the nature of simulation implies safety. Could also disclose rate limits or data freshness.

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 lengthy but well-structured with bullet points and clear sections. It efficiently explains a complex process without unnecessary fluff. Slightly verbose, but every sentence adds value for the intended technical audience.

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 complexity of Monte Carlo simulation, the description covers data source, calibration steps, fallback behavior, and output expectations. It references a sibling tool for default forecasting, setting complete context. With an output schema likely present, this description is fully adequate.

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?

Input schema covers all 4 parameters with descriptions, achieving 100% coverage. The description adds context like 'vectorized numpy simulation paths' and 'percentile forecast bands' that enrich understanding beyond schema, but does not introduce new parameter constraints not already in schema.

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 runs a Monte Carlo price simulation for trading cards, using specific verbs and resource. It distinguishes itself from the sibling 'get_forecast' by positioning as the stochastic Monte Carlo alternative, making the purpose unmistakable.

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 tells when to use this tool vs 'get_forecast': 'For the honest DEFAULT forecast... use get_forecast. This tool is the stochastic Monte Carlo alternative.' It also mentions opt-in, providing clear guidance on tool selection.

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