agent

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

Beyond annotations (readOnlyHint, openWorldHint), the description discloses hard limits (maxSteps, maxUrls, wall-clock), confirmation behavior for pro model, and degraded output when LLM keys or Ollama are missing. This adds significant behavioral transparency.

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 at about 5 lines, with clear sections for usage, behavior, limits, and an example. Every sentence adds value and there is no fluff.

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 complexity (6 parameters, 1 required, nested objects, no output schema), the description covers key behavioral details, limits, edge cases (degraded output), and return type. It is complete enough for an agent to select and use the tool 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?

Schema description coverage is 100%, so the schema already explains each parameter. The description adds a summary and example, but does not provide additional semantic detail for individual parameters beyond what the schema offers. Baseline score of 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 the tool's purpose: an autonomous agent for web research and synthesis without requiring URLs. It distinguishes from other tools like search_web or deep_research by emphasizing autonomy and no need for seed URLs.

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 specifies when to use: when an autonomous agent is needed for web research. It mentions model variations and confirms before pro runs, but does not explicitly compare to sibling tools or state when not to use it. However, the context is sufficient for most agents.

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