blockrun_search

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

Given no annotations, the description discloses pricing model, default behavior, and source options. It references a skill file for more details, but lacks explicit info on error handling, rate limits, or return values.

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 with purpose and uses a clear structure. Some repetition (e.g., pricing mentioned twice) could be trimmed, but it remains efficient for the information provided.

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 tool with no output schema and no annotations, the description covers input well but does not describe return format, error responses, or behavior on invalid inputs. The reference to a skill file partially mitigates this.

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 description adds significant meaning beyond the input schema: it explains the body shape, the purpose of sources, max_results pricing impact, and optional date filters. This compensates for the schema's lack of detail on nested body parameters.

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 performs 'Grok Live Search' for real-time web, X/Twitter, and news with AI-summarized results and citations. It is distinct from sibling tools like blockrun_chat or blockrun_dex.

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 pricing details, default max_results, and how to limit spend. It also mentions using ['x'] for tweet-only searches. While no explicit alternatives are given, sibling tools are sufficiently different to avoid confusion.

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