search_twitterapi_docs

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

No annotations provided, so the description carries full burden. It details that the tool returns 'Ranked results with endpoint paths, descriptions, and relevance scores' and supports camelCase/underscore. It could mention rate limits or authentication, but the read-only search nature is implied.

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 concise and well-structured: a brief statement, 'USE THIS WHEN', 'RETURNS', and examples. Every sentence serves a purpose, and the format is front-loaded with essential information.

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?

Given the tool's simplicity (2 parameters, no nested objects), the description fully covers purpose, usage, return value, and examples. It integrates well with sibling tools and provides enough context for an AI agent to select and invoke correctly.

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 has 100% coverage with good descriptions. The description adds value by providing example queries, specifying English keywords, and offering usage guidance for max_results (e.g., 'higher values for comprehensive research, lower for quick lookups').

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 it searches TwitterAPI.io documentation for endpoints, guides, and blog posts. It distinguishes from sibling tools (e.g., get_twitterapi_endpoint, get_twitterapi_guide) by targeting across the entire documentation, with examples like 'advanced search' and 'rate limit'.

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 explicitly includes 'USE THIS WHEN: You need to find information across the entire documentation,' providing clear context. It does not explicitly mention when not to use it or alternatives, but the sibling tool list implies those for specific lookups.

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