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

Beyond the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false), the description discloses extensive behavior: it walks the order-book ladder, returns specific metrics (top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd), and explains the risk of partial basket fills converting an arb into directional risk. This goes far beyond what annotations alone convey.

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 SINGLE-MARKET and BASKET sections. Every sentence carries substantive guidance, but it could be slightly trimmed for brevity. The front-loaded purpose sentence and the explicit 'USE THIS' directive make it actionable despite the length.

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?

Despite having no output schema, the description enumerates all key return fields for both modes (top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, verdict; theoretical_sum, realizable_sum, capture_ratio, profit_usd, per-leg fill detail, thin_legs, max_clean_notional_usd, forced_directional_risk). It also covers all four parameters, default behaviors, and safety warnings, making it fully self-contained for an AI agent.

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?

Even though the schema has 100% parameter description coverage, the tool description adds significant semantics: it explains the dual-mode interpretation of `side`, clarifies that `size_usd` means 'max spend' for buys and 'target proceeds' for sells, and for basket mode defines `size_usd` as settlement notional S with shares paying $1. It also documents the default (1000) and clamp range (10–1,000,000), which the schema omits.

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 function: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It specifies two modes (single-market and basket) and explicitly distinguishes itself from sibling tools like polymarket_arbitrage and polymarket_edges by positioning itself as the pre-trade risk check for those signals.

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 when-to-use guidance: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It also explains why it's necessary (theoretical overround on thin books is not capturable; partial basket fills create unhedged directional risk), which effectively communicates when alternatives are insufficient.

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