funnel_optimizer

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

With no annotations, the description fully bears the burden of behavioral disclosure. It explicitly states the tool is read-only, stateless, idempotent, and safe to call repeatedly. It also mentions the free tier rate limit (10/day) and pro tier unlimited access, plus that no authentication is required for basic usage. This is comprehensive.

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 well-structured with clear sections: main purpose, Args, Behavior, When to use, When NOT to use. Every sentence adds value, and the text is concise without extra 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 tool's complexity (2 parameters, no output schema), the description covers behavior, parameters, and usage well. However, it does not specify the exact output structure (e.g., JSON format), only mentioning the output conceptually ('identify the biggest leak point with optimization recommendations'). This is a minor gap.

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 coverage is 0%, so the description must compensate. The 'stages' parameter is explained with a clear example: 'List of funnel stages as [{"name": "Awareness", "count": 10000}, ...]'. The 'api_key' parameter is implicitly addressed via the note on authentication, but its exact role (e.g., for pro tier) is ambiguous. Overall, the description adds significant meaning beyond the bare schema.

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: 'Analyze a conversion funnel and identify the biggest leak point with optimization recommendations.' It specifies the verb (analyze, identify) and resource (conversion funnel), and the output is well-defined. The purpose distinguishes it from sibling tools like ab_test_analyze or attribution_model, which focus on different aspects.

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 includes 'When to use' and 'When NOT to use' sections, providing context on appropriate scenarios. It advises against real-time production use without human review. However, it does not explicitly compare this tool to siblings, leaving room for ambiguity in tool selection.

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