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

With no annotations, the description carries the burden of behavioral disclosure. It explains that results are normalized, that raw venue fields are preserved, and that it returns a specific list of fields. This adds useful context beyond the schema, though it omits potential latency/async behavior, which is already visible in the schema.

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 two sentences, front-loads the core purpose, and every phrase adds value. There is no wasted words or repetition of schema content.

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 moderately complex cross-venue search tool with 6 parameters and no output schema, the description covers the core behavior, output fields, and normalization benefit. It lacks explicit mention of edge cases or pagination, but the parameter schema fills most gaps, making this reasonably complete.

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 does not add parameter-level details beyond what the schema already provides. It mentions the output shape, which relates indirectly to parameters like 'venues', but does not enhance parameter understanding.

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 uses a specific verb ('Search'), specifies the resource ('live prediction markets'), and clearly defines the scope ('across Polymarket and Kalshi in one call'). It also mentions the normalized output shape, which distinguishes it from single-venue sibling tools like kalshi_markets and polymarket_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?

The description clearly implies when to use the tool: when you need to query multiple prediction market venues simultaneously and avoid reconciling different formats. However, it does not explicitly name alternatives or provide 'when not to use' guidance, stopping 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.