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

Annotations already indicate read-only, open-world, idempotent, and non-destructive behavior. The description adds substantial context: it details the 'walk the ladder' process, explains return fields (vwap_fill_price, slippage_pp, etc.), highlights risks (thin legs, forced directional risk), and confirms it does not execute trades. No contradictions 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 description is long but well-structured with clear sections (SINGLE-MARKET, BASKET) and front-loaded 'REQUIRES' and 'USE THIS' directives. Every sentence adds necessary context, though some brevity could be achieved without losing clarity. It is appropriately concise for a complex tool.

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?

The tool has no output schema, so the description must cover return values, which it does thoroughly (top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, verdict for single-market; theoretical_sum, realizable_sum, capture_ratio, profit_usd, per-leg fill detail, thin_legs, max_clean_notional_usd, forced_directional_risk for baskets). It also covers edge cases and risks, making it complete for an AI agent to decide usage.

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 100%, but the description adds significant value by explaining parameter semantics in context: size_usd is 'settlement notional S' for baskets, side defaults to 'auto' based on partition sum, and the market/event distinction is reinforced with mode-specific behavior. This goes far beyond the schema descriptions.

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 explicitly states the tool's purpose as a 'realizable-vs-theoretical edge check against live CLOB order-book depth'. It clearly distinguishes single-market and basket modes, specifies the outputs (top_of_book, vwap_fill_price, etc.), and ties usage to specific sibling tools (polymarket_arbitrage, polymarket_edges). The verb 'check' and resource 'order-book depth' are precise and actionable.

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?

The description provides explicit conditions: 'REQUIRES one of market or event', explains when to use (before arbitrage signals or trades above $500), and warns against misuse ('partial basket fills convert an arb into an unhedged directional position'). It also clarifies default behavior for basket mode when side is omitted. This is comprehensive guidance.

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