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

Even though annotations already declare readOnly, idempotent, and non-destructive, the description adds crucial behavioral context: it walks the order-book ladder, returns verdicts (clean|degraded|cannot_fill), and warns that partial basket fills convert an arb into unhedged directional risk—the dominant loss mode. This goes well beyond the annotation hints.

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 but extremely efficient. It front-loads the core purpose, then uses structured sections (SINGLE-MARKET, BASKET) and imperative guidance. Every sentence adds unique information—no filler—making the length justified by the tool's complexity.

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 fully enumerates return values for both modes (top_of_book, vwap_fill_price, slippage_pp, theoretical_sum, capture_ratio, ...). It also covers prerequisites, defaults, and practical risk context, giving an AI agent everything needed to invoke and interpret results 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%, but the description adds significant semantic nuance: it explains mode-dependent interpretations of `size_usd` (max spend vs target proceeds vs settlement notional), side defaults and auto-detection for baskets, and clarifies the `market` vs `event` parameter distinction. This enhances what the schema alone provides.

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 siblings by explicitly referencing polymarket_arbitrage and polymarket_edges, and explains both single-market and basket modes.

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?

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 when not to rely on it, citing thin-book overround and partial-fill risks, making alternatives and exclusions clear.

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