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

With no annotations, the description carries the full burden and does well: it discloses the on-chain perpetual pricing model (0–1 USDC probability shares), the possible status values (active/settlement/delisted), the returned fields, and an explicit per-call cost of $0.002 USDC — a behavioral trait an agent must know before calling.

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?

Three tight sentences, front-loaded with what it lists, followed by return fields, then the pricing model, then cost — every sentence adds information an agent would otherwise lack.

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 usefully enumerates returned fields and adds the paid-call detail. The one gap is scale behavior: a no-parameter 'list all' tool says nothing about result size limits, pagination, or truncation.

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 tool takes zero parameters, so there is nothing to disambiguate; the baseline applies and the description correctly spends its words elsewhere.

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 and resource ('List all Drift Protocol BET prediction markets on Solana') and scopes it as the full-market enumeration, which separates it from detail/history siblings like drift_market_details and drift_market_history.

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?

'List all' implies the use case is enumeration of the whole market universe, but the description never states when to prefer this over drift_market_details, prediction_markets_trending, or prediction_market_events, and gives no exclusions or prerequisites.

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