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

Annotations already declare readOnlyHint=true (safe), idempotentHint=true, and destructiveHint=false. The description adds significant behavioral context beyond annotations: it details the internal walking of the order-book ladder, the verdict system (clean|degraded|cannot_fill), and for basket mode, the risk of forced_directional_risk. This provides transparency about what the tool computes and its limitations.

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: a clear opening sentence, separated single-market and basket sections using uppercase headers, and a conclusion with usage guidance. Every sentence adds value; there is no fluff. However, it could be slightly more concise by breaking into bullet points for readability, given the density.

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, but the description comprehensively lists all return fields for both modes, including advanced concepts like capture_ratio, thin_legs, max_clean_notional_usd, and forced_directional_risk. It also warns about the dominant loss mode in arb-bot P&L. Given the tool's complexity and the absence of output schema, the description provides a complete mental model.

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%, so baseline is 3. The description adds meaning by explaining how parameters behave differently in single-market vs basket modes (e.g., size_usd interpreted as 'max spend on buys, target proceeds on sells' vs 'settlement notional shares per leg'), default values, and the auto-detection of side in basket mode. This goes beyond the schema's brief 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 clearly states the tool performs a 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It distinguishes between single-market and basket modes, and explicitly lists what it returns (top_of_book, vwap_fill_price, slippage_pp, etc.). This differentiates it from sibling tools like polymarket_arbitrage and polymarket_edges.

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 says 'USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500.' It also explains why (theoretical overround on thin books is not capturable, partial fills create unhedged directional positions), providing clear when-to-use and when-not-to-use guidance.

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