blockrun_price

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

The description adds significant context beyond annotations: it discloses the data source (Pyth-backed), pricing model (free vs paid), and action constraints (market required for stocks). It does not contradict any annotations. The behavior is fully transparent.

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 well-structured with bullet points for actions, pricing, and markets, plus explicit examples. It is moderately concise but contains some redundancy (e.g., restating action options). Front-loaded with purpose.

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 11 parameters and no output schema, the description should describe return structures. It mentions 'realtime quote' and 'OHLC bars' but lacks detail on the exact fields returned. The completeness is adequate but not thorough for a data-heavy 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?

Input schema coverage is 100%, so baseline is 3. The description adds value by showcasing parameter combinations in examples, clarifying resolution defaults, and explaining the market parameter's conditional requirement. This goes beyond the schema's individual descriptions.

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 the tool provides realtime quotes and OHLC history for multiple asset classes (crypto, FX, commodities, stocks). It specifies three distinct actions (price, history, list) and lists supported markets. This distinguishes it from sibling tools like blockrun_markets or blockrun_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?

The description gives explicit guidance on when to use each action and notes pricing differences. It explains that market is required for stocks and provides usage examples. However, it does not explicitly state when not to use this tool compared to alternatives.

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