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

While the annotations cover safety, the description adds behavioral context regarding the workflow, specifying that the final 'sealed verdict' occurs in the local Lab, pointing to the next operational step for the agent.

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 text is highly dense and avoids fluff. It packs the tool's entire conceptual mandate—protocol, safety, and workflow—into a few efficient sentences.

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?

As a reference tool with no inputs, its completeness lies in providing the conceptual framework. The description successfully delivers the necessary protocol guidance for the agent to understand its context before proceeding to generation.

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?

Since the tool has zero input parameters, the description cannot add semantic value to any input. Following the rule for 0 parameters, it receives the baseline score of 4.

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 defines the tool as a 'short reference' for the ArenaScript protocol, making it distinct from sibling tools like 'generate_arenascript_strategy' or 'validate_arenascript.' It establishes its role as a foundational guide.

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 provides explicit usage guidance, instructing the AI to call it 'before generating a strategy.' It outlines the precise workflow (generate → validate → backtest → Monte Carlo).

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