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

Annotations already declare readOnly/non-destructive behavior, but the description adds substantial behavioral context: it explains the outputs, the meaning of risk_penalty_pct, the provable relationship between pyramid_risk and clean_entry_risk, and the liquidation_before_stop condition. No contradiction with annotations.

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 purpose is front-loaded and the dense output explanations are relevant for a tool with no output schema. It is longer than ideal, but nearly every clause adds decision-useful semantics rather than 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?

For an 11-parameter analytical workflow with no output schema, the description carries the return-value burden well: it names and explains the blended average, liquidation/breakeven, margin_added, risk figures, risk_penalty_pct, and liquidation_before_stop. Enough context is provided to call and interpret the tool.

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 91%, so parameter semantics are already well documented. The description adds only marginal context for add_price, stop_loss, and existing_entry_price, mostly repeating what the schema already says.

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 names the exact decision-analysis purpose: comparing an average-down add against a fresh entry for the same final size. It specifies the inputs it reasons over and the metrics it produces, which clearly separates it from generic entry/sizing 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?

It gives explicit user-phrasing triggers ("should I add to this losing position?" and "what does averaging down actually cost me here?") and scopes the tool to already-open positions. It does not explicitly name sibling alternatives or state when not to use it.

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