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

Even though annotations already declare read-only, open-world, idempotent, and non-destructive behavior, the description adds significant detail: it walks the order-book ladder, returns specific fields for each mode, and warns about forced directional risk in basket mode. The description also notes the requirement to pass exactly one of market or event, and explains how size_usd is interpreted differently depending on mode.

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 densely packed. It uses clear structural markers (SINGLE-MARKET, BASKET) and every sentence adds essential information. Given the tool's two modes, many output fields, and nuanced risk rationale, the length is justified and well-organized.

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 carries the full burden of explaining return values, and it does so thoroughly for both modes (lists all key fields like top_of_book, vwap_fill_price, slippage_pp, shares_filled, verdict, theoretical_sum vs realizable_sum, capture_ratio, etc.). It also covers parameters, defaults, and usage context, making the tool fully understandable without supplemental documentation.

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?

While the schema covers all parameters, the description enriches them by explaining the meaning of side in both modes (e.g., default auto for basket), the interpretation of size_usd (max spend vs. target proceeds vs. settlement notional), and the required mutual exclusivity of market and event. It adds practical context beyond the schema definitions.

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's purpose: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It specifies two distinct modes (single-market and basket), names the exact output metrics, and distinguishes itself from siblings like polymarket_arbitrage and polymarket_edges by focusing on fill risk rather than opportunity detection.

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?

Explicit usage guidance is provided: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' The description explains why this tool is necessary (theoretical overround on thin books is not capturable) and highlights the risk of partial basket fills, giving clear before-when and rationale.

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