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

Goes well beyond the readOnly/openWorld annotations by disclosing result size (up to 20), ranking basis (24h volume), outcome truncation logic (up to four outcomes, leaders or price-ladder rungs nearest 50%), and multiple exclusion rules (settled-looking events at 99%+, game prop sheets, sports/esports singles unless that category is requested, Up or Down and tweet-count markets). It also frames the output as crowd forecasts, not advice.

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 trigger conditions before the mechanics, which is the right order. It is dense and slightly repetitive at the end (the 'not advice' and 'do not use to choose a market' sentences overlap), but nearly every sentence carries filtering or scope information.

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?

Despite an output schema existing, the description still tells the agent what each returned event contains (probabilities, 24h change, volume) and what is deliberately absent, which is exactly the context needed to interpret a filtered feed. Nothing an agent needs to call or trust the result is missing.

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 baseline is 3, but the description adds real semantics: the category filter is optional and materially changes what is included (sports/esports singles appear only when that category is selected), and the limit is bounded at 20. It doesn't restate the enum values or the default of 8, but it does explain the behavioral effect of category.

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+resource (returns trending Polymarket events ranked by 24h volume) and immediately scopes it against siblings like search_markets and get_market_movers by emphasizing 'trending/popular/hot' and a 24-hour volume window. An agent can distinguish it from get_market_movers and search_markets without opening any schema.

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?

Gives concrete trigger phrases ('what's trending on Polymarket', 'top crypto markets right now') plus explicit exclusions: do not use it to pick a market or trader to invest in, or when the user asks which market to buy. This is a full when/when-not contract.

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