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

With no annotations provided, the description carries the full burden. It discloses the cost ($0.01 per call, free on failure/empty), clarifies it provides facts only and is not investment advice or a price target/signal. This is useful behavioral context beyond what the schema offers. It does not mention rate limits or authentication details beyond pointing to buy_credits, but the cost and disclaimer are significant.

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 efficient and well-structured. It front-loads the primary purpose and return data, then adds cost and disclaimer details in separate sentences. Every sentence adds value: purpose, data scope, disclaimer, cost, and funding path. There is no wasted wording.

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 having no output schema, the description lists the key return fields (implied probability, 24h change, volume, close date, URL), so the agent knows what to expect. It covers cost, failure behavior, and how to get credits. For a simple two-parameter tool, this is comprehensive and leaves no critical gap for an agent to call it 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 description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond what the schema already provides: q is a ticker or company name, limit is a number with default 20. The description restates the q semantics but adds nothing new, so it stays at baseline.

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 clearly states the verb (Open) and resource (prediction markets mentioning a US stock ticker or company), explicitly covering both Polymarket and Kalshi in one call. It lists the exact data returned (implied probability, 24h change, volume, close date, URL), which distinguishes it from siblings like pm_odds or pm_search that likely serve different scopes. This is a specific and unambiguous purpose.

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 implies when to use it: for prediction markets on US stocks, combining two platforms. It provides context on how to fund usage (buy_credits or /buy/credits) and states the cost model. However, it does not explicitly mention alternatives or when NOT to use this tool versus pm_odds or pm_search. The usage guidance is clear but lacks explicit exclusions.

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