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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, but the description adds critical context beyond these: it warns that 'partial basket fills convert an arb into an unhedged directional position' and that 'theoretical overround on thin books is not capturable.' These insights are not evident from annotations alone and significantly enhance the agent's understanding of potential risks.

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?

Though the description is relatively long, it is front-loaded with the core purpose and systematically organized into requirements, mode-specific behavior, outputs, and usage guidance. Every sentence contributes value—there is no redundancy or filler. The density is justified by the tool's complexity and the absence of an output schema.

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?

With no output schema, the description compensates by enumerating all return values for both modes (top_of_book, vwap_fill_price, slippage_pp, verdict, etc. for single-market; theoretical_sum, realizable_sum, capture_ratio, thin_legs[], etc. for basket). It also covers edge cases like thin legs and forced directional risk, plus the size clamp, making the description self-contained and actionable.

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 coverage is 100%, but the description goes far beyond the schema definitions. It explains that exactly one of market or event is required, interprets size_usd differently in single-market (max spend vs target proceeds) versus basket (settlement notional), and clarifies side defaults and auto-selection logic. This adds substantial meaning to each parameter beyond the basic 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 opens with a specific verb+resource: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It clearly distinguishes itself from sibling tools like polymarket_arbitrage and polymarket_edges by focusing on fill risk and slippage, and it details two distinct modes (single-market and basket), making its purpose unambiguous.

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 explicitly states when to use the tool: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It names the alternative tools and explains the rationale (thin books, partial fills), providing clear context for when it is needed versus when it may be unnecessary.

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