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

The description goes well beyond the annotations (readOnlyHint, idempotentHint, etc.) by describing the actual behavior: it 'walks the ladder' on the order book, returns specific metrics like top_of_book, vwap_fill_price, slippage_pp, shares_filled, and warns of the risk that 'partial basket fills convert an arb into an unhedged directional position.' It also discloses the identification of forced_directional_risk. This rich operational detail is not present in the annotations.

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 lengthy, but it's well-structured with clear sections for single-market and basket modes, and it front-loads the core purpose and usage requirements. Every sentence carries critical safety, output, or mode-specific information. While it could be tightened, the density is justified by the tool's complexity and the absence of an output schema.

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?

Given there is no output schema, the description fully compensates by enumerating output fields for both modes (e.g., top_of_book, vwap_fill_price, shares_filled, capture_ratio, thin_legs, max_clean_notional_usd, forced_directional_risk). It also explains edge-case risks like overround on thin books and the dominant loss mode from partial basket fills. This is a complete and self-sufficient explanation of the tool's behavior and results.

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?

The schema covers all parameters with descriptions, so the baseline is 3. The description adds meaningful semantic distinctions: for `size_usd`, it clarifies different meanings in single-market (max spend on buys, target proceeds on sells) vs. basket (settlement notional — shares per leg), and explains the `side` default auto behavior in basket mode. It also highlights the mutual-exclusivity of `market` and `event`. This additional context enhances parameter understanding beyond the schema.

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 and clear purpose: 'Realizable-vs-theoretical edge check against live CLOB order-book depth.' It explicitly positions itself as a pre-trade validation for signals from sibling tools (polymarket_arbitrage, polymarket_edges), clearly distinguishing its function. The verb-resource pairing is unambiguous and comprehensive.

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 further details the two modes (single-market vs. basket) and the required inputs for each, giving clear context on when each mode is appropriate. This goes beyond mere implication and offers actionable direction.

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