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

Annotations already establish it as a safe read (readOnlyHint=true), and the description adds rich behavioral context beyond that: it explicitly flags the single-snapshot limitation (no modeling of book refill between clips), discloses the comparative output full_size_price_impact_pct, and states the payment model (USDC on Base).

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?

Front-loaded with the core action and target, followed by output, limitation, input-resolution, and payment notes in a tight sequence. Every sentence carries distinct information with no filler.

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?

An output schema exists, so return-value detail in prose is unnecessary, and annotations cover the safety profile. The description is nonetheless complete: it covers the calculation method, its key caveat, input resolution, and cost of use for what is a fairly complex 6-parameter tool.

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 the schema already documents all six parameters (baseline 3). The description adds genuine meaning beyond the schema by defining the token_id vs market_slug resolution path, the 'exact slug only, no fuzzy keyword search' constraint, and the default behavior of max_price_impact_pct_per_slice.

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?

States a specific verb (recommend split/clip count) applied to a specific resource (a Polymarket outcome's live order book for a size). The function is distinguishable from siblings like prediction.exit_capacity_audit or prediction.hip4_price, which measure capacity or price rather than optimal clip splitting.

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?

Explains the context for using it (controlling per-clip price impact for a large position) and how to supply the token (raw token_id or market_slug+outcome, exact slug only). It does not explicitly name alternative tools or state when NOT to use it, so it stops short of a 5.

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