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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description does not contradict these. It adds rich behavioral context: it walks the order book ladder, returns specific metrics (top_of_book, vwap_fill_price, slippage_pp, shares_filled, etc.), and highlights risks like thin_legs and forced_directional_risk. It also explains behavioral nuances like size_usd interpreted differently in single-market vs basket modes.

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 dense and information-rich but runs long as a single paragraph. Every sentence contributes value—mode details, defaults, outputs, and usage guidance—but it could be more scannable with bullet points or section breaks. Still, given the tool's complexity (two modes), thoroughness is justified and no fluff exists.

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 is complex (two modes, four params, no output schema), and the description fully compensates: it lists all return values (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), explains parameter defaults and clamping, and provides decision-relevant context like the dominant loss mode. An agent has everything needed to select and invoke correctly.

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%, so baseline is 3, but the description significantly exceeds the schema by explaining mode-specific semantics. For example, it defines side defaults and auto behavior ('default auto — sell if partition sum > 1, buy if < 1'), clarifies size_usd as 'max spend on buys, target proceeds on sells' vs 'settlement notional' for baskets, and notes the clamp range. This adds substantial meaning beyond the schema fields.

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 uses a specific verb ('check') and resource (order-book depth), and distinguishes itself from siblings by explicitly referencing polymarket_arbitrage and polymarket_edges as tools to precede it. The two modes (single-market and basket) are clearly delineated.

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 when-to-use guidance is provided: 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It also explains the rationale (theoretical overround on thin books is not capturable) and the risk of partial basket fills, effectively teaching the agent when this tool is necessary.

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