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

With no annotations, the description carries the full burden, and it does disclose the key behavioral trait: three sources are queried at once and probabilities come back per source so odds can be compared. It is silent on failure modes (what if one venue is unreachable), rate limits, auth requirements, and whether results are interleaved or grouped by platform.

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?

Two sentences, no filler, and the resource scope is front-loaded before the usage hint. The 'so real-money and crowd odds can be compared' clause arguably restates the value rather than adding instruction, but the text is tight overall.

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?

An output schema exists, so return-value explanation is legitimately omitted. What remains missing is result-count semantics for 'limit' and how to attribute a returned event to its venue — details an agent needs to interpret an aggregated multi-source response 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 coverage is 0%, so the description must compensate for both parameters and does not. 'q' is inferable from context, but 'limit' (default 5) is never explained — per-venue or total, and what happens when it is raised — leaving a real ambiguity in how many results come back from each market.

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?

Names a specific action and resource — a single search that fans out across Polymarket, Kalshi and Manifold — and states what it returns: matching open events and markets with current probabilities from each source. That implicitly separates it from the platform-specific siblings (polymarket_search, kalshi_search, manifold_search), though it never names them, so an agent must infer the distinction.

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 line "Use to answer 'what are the odds that...'" gives a clear triggering intent, and the aggregation framing implies cross-platform comparison. But it never states when NOT to use it or points to the per-platform siblings for deeper single-venue data, which is exactly the choice an agent faces given three sibling search tools.

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