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

No annotations exist, so the description carries the full behavioral burden. It usefully discloses that the call is FREE and that it returns live (not historical) data plus the specific fields, but says nothing about rate limits, error behavior for an invalid slug/ticker, or coverage of closed/settled markets.

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 compact sentences, with the high-value 'FREE' signal and the single-market scope front-loaded. Nothing is wasted.

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?

For a one-parameter lookup with no output schema, the description names the returned fields (price, volume, close time) and the schema-format used, which is enough for an agent to call it correctly. Minor gaps remain around failure cases and data freshness guarantees.

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% and the single parameter is documented with two concrete format examples (slug and ticker). The description's instruction to supply a slug or ticker largely restates the schema, so it adds little beyond 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?

States a specific retrieval verb and the exact resource: live price, volume and close time for a single market in a normalised Polymarket+Kalshi schema. The 'ONE prediction market' framing distinguishes it from siblings like live_markets and search_markets that clearly operate on multiple markets.

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?

'Give a Polymarket slug or a Kalshi ticker' tells the agent the precondition for calling it, and 'ONE' implies bulk listings belong elsewhere. It stops short of explicitly naming live_markets or search_markets as the alternatives for multi-market queries, so it is context-rich but not full when/when-not guidance.

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