ask_perplexity_to_learn

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

No annotations are provided, so the description carries the full burden. It mentions internet access and a teaching approach but does not disclose whether the tool is read-only, has rate limits, or any restrictions. As a learning tool, it is likely read-only, but this is not explicitly stated.

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 structured with bullet points and examples, making it easy to scan. It front-loads the purpose. While slightly lengthy, every sentence adds value, earning a score of 4.

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 presence of an output schema, the description does not need to detail return values. It covers purpose, usage guidelines, parameter semantics, and even mentions internet access. For a learning tool, it is comprehensive and well-rounded.

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?

With 0% schema description coverage, the description adds significant meaning by explaining the 'prompt' parameter as the question and the 'model' parameter as a Sonar model with options listed. It provides helpful context beyond the schema's basic type information.

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's purpose: 'Learn complex concepts with pedagogical explanations, examples, and analogies.' It uses a specific verb ('learn') and resource ('concepts'), and distinguishes itself from siblings like 'ask_perplexity' by emphasizing a teaching-optimized approach.

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 this tool, stating it is 'teaching-optimized' and listing examples of good prompts. However, it does not explicitly state when not to use it or mention alternative tools, but the implied usage is clear enough for an agent.

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