elfatwitterintelligenceagent_search_mentions

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully adds that results are limited to 'influential ones' and 'does not contain all tweets,' which are important constraints not in the schema. However, it doesn't mention rate limits, authentication needs, or what the output format looks like (no output schema exists), leaving some behavioral aspects unclear.

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 appropriately sized and front-loaded with the core purpose. The sentences about keyword formatting are necessary but could be more streamlined. Overall, it's efficient with minimal waste, though the keyword instructions are somewhat repetitive.

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 moderate complexity (3 parameters, no annotations, no output schema), the description provides adequate context about purpose, constraints, and usage. However, it lacks details on output format, error handling, or deeper behavioral traits that would be helpful for an agent to fully understand how to interpret results.

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 description coverage is 100%, so the schema already documents all three parameters. The description adds some semantic context by specifying that keywords should be 'one word or phrase,' 'maximum of 5 keywords,' and 'one key word should be one concept,' which provides guidance beyond the schema's basic array description. This justifies a baseline 3 with slight enhancement.

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 searches for mentions of specific tokens or topics on Twitter, focusing on cryptocurrencies/blockchain and influential accounts. It distinguishes from sibling tools like 'search_account' or 'get_trending_tokens' by emphasizing content search rather than account lookup or trending analysis. However, it doesn't explicitly contrast with all siblings, keeping it at 4 rather than 5.

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 clear context for when to use it: 'when you want to understand what influential people are saying about a particular token or topic on Twitter.' It doesn't explicitly state when NOT to use it or name specific alternatives among siblings, but the context is sufficiently clear for an agent to infer appropriate usage scenarios.

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