blockrun_search

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

Beyond the readOnly/openWorld/destructive annotations, the description discloses pricing, cost calculation, defaults, lower/upper bounds on max_results, and source behavior. This gives an agent crucial cost and scope information before invocation.

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 front-loaded and most sentences carry useful cost or request-shape information. However, it ends with an incomplete sentence ('Full request shape + worked examples in the') and the pricing block is longer than strictly necessary.

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 agent can construct a valid call: body shape, sources, max_results bounds, and date formats are all provided, and the readOnly annotations cover safety. It falls short of full completeness because the promised full request shape/examples are cut off and the return payload is only vaguely described as AI-summarized results with citations.

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 coverage is high but terse; the description adds real semantics for the body parameter: query, sources array choices, max_results range/default, and date format. It effectively documents the nested request body that the schema leaves implicit.

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 opening line identifies a specific function: real-time web/X/Twitter/news search with AI-summarized results and citations. It does not explicitly name sibling search tools like blockrun_exa, so it falls just short of full sibling differentiation.

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?

Provides practical guidance: use ['x'] for tweet-only searches, set max_results to control cost, and 3 sources is often enough for a plain fact. However, it never explains when to prefer this tool over blockrun_exa/surf or when not to use it, leaving cross-tool routing mostly to inference.

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