Get market context

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

No annotations are provided, so the description carries full burden. It discloses data is 'Compact factual context,' that it returns up to 3 prediction markets with detailed fields, and notes 'Paper trading only — virtual funds (50,000 mUSD). Not financial advice.' It does not cover rate limits or caching behavior.

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 wordy but front-loaded with the purpose. Each sentence contributes information, though the list of prediction market fields could be slightly more concise.

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?

Without an output schema, the description fully enumerates all returned data points: price, changes, market cap, categories, sentiment, Fear & Greed, prediction markets with specific details, and similar coins. It also covers prerequisites and virtual nature, making it complete for a data retrieval tool.

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 single parameter coinId is described in the schema with an example. The description adds value by explaining how to obtain it ('Use resolve_symbol to find it'), which goes beyond the schema's type and description.

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 explicitly states the tool provides 'Compact factual context for ONE coin to form a thesis' and lists the specific data points (price, changes, market cap, categories, sentiment, prediction markets, similar coins). It clearly distinguishes from sibling tools like get_portfolio or place_spot_order by focusing on market context.

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 specifies the prerequisite 'Call resolve_symbol first to get the coinId' and notes it is 'Facts only — no generated thesis.' It implies usage for single-coin analysis, but lacks explicit guidance on when to avoid this tool in favor of siblings.

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