prediction_market_detail

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

With no annotations provided, the description uses 'Get' to signal a read-only operation and names the key included field (token_id). It adds a practical downstream dependency note, though it does not discuss error cases or permissions.

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 three short sentences: a summary line, an Args block, and a dependency note. No filler; all content is useful.

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 detail endpoint with an output schema, the description fully covers purpose, parameter format, and downstream usage. The token_id note supplies the key integration detail needed by sibling tool prediction_price_history.

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 only parameter, slug_or_id, is explained as a 'Market slug (from a polymarket.com URL) or numeric id,' adding meaningful format and source context beyond the schema's bare string type. This compensates for the 0% schema description coverage.

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 opens with 'Get full detail for one prediction market' using a specific verb and resource, and explicitly notes outcome token ids. This distinguishes it from sibling list/search tools like prediction_markets and prediction_search.

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?

It clearly defines the target use case—retrieving a single market's full detail—and connects the result to prediction_price_history via token_id. It does not explicitly list exclusions or alternatives, but the context is unambiguous given the sibling set.

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