exponential_pdf

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool calculates a PDF but doesn't describe output format, error handling, computational limits, or assumptions (e.g., rate > 0). For a statistical tool with zero annotation coverage, this is a significant gap in transparency about how the tool behaves beyond its basic function.

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 extremely concise and front-loaded in a single sentence: 'Calculate the probability density function (PDF) of the exponential distribution (Domain: probability, Category: general).' Every word contributes essential information without waste, making it efficient and well-structured for quick understanding.

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 of a statistical tool with no annotations, no output schema, and low parameter coverage, the description is incomplete. It states the purpose but lacks details on behavior, parameters, output, or usage context. For a tool that performs calculations with mathematical assumptions, more information is needed to ensure correct invocation and interpretation.

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?

The description adds no information about parameters beyond what the input schema provides. With 0% schema description coverage and two parameters (x, rate), the schema only defines types and defaults. The description doesn't explain what x represents (e.g., input value) or rate (e.g., λ parameter), leaving semantics undocumented. This fails to compensate for the low schema coverage.

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: 'Calculate the probability density function (PDF) of the exponential distribution.' It specifies the verb ('calculate'), resource ('PDF'), and domain ('probability, Category: general'), making it unambiguous. However, it doesn't differentiate from sibling tools like 'exponential_cdf' or 'exponential_sample', which are related but distinct operations, preventing a perfect score.

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 no guidance on when to use this tool versus alternatives. It mentions the domain ('probability') but doesn't specify scenarios, prerequisites, or comparisons to sibling tools like 'exponential_cdf' (cumulative distribution) or 'normal_pdf' (other distribution). This lack of context leaves the agent without explicit usage instructions.

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