ask_oracle

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

No annotations are provided, so the description must disclose behavior. It states the tool returns an estimated probability, key factors, and reasoning, which is sufficient for a read-only query tool. It does not disclose rate limits or auth, but those are not critical for this simple tool.

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 long, each sentence adding essential information: the action and return values in the first, the domains in the second. No wasted words.

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?

With an output schema present (not shown), the description complements it by listing key return fields. For a single-parameter tool, the description fully informs about usage and return values. No gaps remain.

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?

The input schema has one parameter 'question' with 100% description coverage. The description adds value by specifying the expected format ('a yes/no market question') and providing an example, which aids correct usage beyond the schema.

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 it asks an oracle for a probability estimate on yes/no market questions, lists return fields (estimated probability, key factors, reasoning), and specifies applicable domains (crypto, macro, Polymarket). It is distinct from sibling tools like get_market_brief or get_market_sentiment.

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 provides clear context: it works for yes/no market questions and gives example domains. However, it does not explicitly state when to avoid this tool or compare it to siblings, though the sibling names imply different scopes.

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