ask_neariq

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

No annotations are provided, so the description carries full burden. It mentions the AI has 'full context of your dashboard data' but does not disclose whether it modifies data, has rate limits, or requires specific permissions. Safety profile is 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?

Two sentences, no wasted words. Front-loaded with purpose. Could be slightly more structured, but efficient overall.

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 no output schema, more details on response format would help. However, for a simple Q&A tool, it covers core purpose. Missing info on how to use the context parameter effectively.

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 fully describes both parameters (message, context) with descriptions. The description adds marginal value by grouping question topics, but schema coverage is 100%, so baseline 3 is appropriate.

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 asks an AI assistant about business, competitors, market, or strategy. It is specific about topics and distinguishes from sibling tools that retrieve specific data (e.g., get_behavioral_signals). However, 'ask a question' is somewhat generic.

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?

It implies use when you have a question needing AI context, but lacks explicit guidance on when not to use it or how it differs from alternatives like get_ai_visibility or get_behavioral_signals.

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