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

No annotations are provided, so the description carries the full burden. It does disclose the response shape and the fact that only 'open questions' are returned, which is useful behavioral context for a read-only search, but says nothing about result ordering, pagination past the limit, or whether resolved markets are accessible.

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, front-loaded with the verb and resource, with no wasted clauses. The 'largest play-money prediction community' phrasing is mildly promotional but does help the agent understand the data's nature (play money, not real money).

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 not strictly required, yet the description still names the key fields. For a two-parameter search tool this is nearly complete; only the missing guidance on query formatting and result limits keeps it below 5.

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 0%, so both parameters are undocumented. The topic list ('AI, tech, science, politics') hints at what 'q' accepts, but neither the query syntax nor the semantics/ceiling of 'limit' are explained. The parameter names are largely self-evident and limit has a default, so this is a modest rather than severe gap.

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 and resource ('Search Manifold Markets') plus the scope ('open questions') and the fields returned (probability, volume, bettor count, close date). It implicitly distinguishes itself from the real-money prediction siblings, though it never names polymarket_search or kalshi_search outright.

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?

'Use for crowd forecasts on topics real-money markets don't cover' gives a clear selection rule against the real-money alternatives. What's missing is an explicit named alternative and an statement of what this tool should not be used for.

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