np_log

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

No annotations provided, so the description must disclose behavioral traits. It mentions 'element-wise' but omits details on handling non-positive inputs (e.g., negative numbers or zero), which is critical for a logarithm 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?

Extremely concise: one sentence with minimal word count. Every word adds value, no redundancy. Front-loaded with key information.

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?

With an output schema present, return values are not needed. However, the description lacks edge-case behavior (e.g., NaN for negative inputs) and prerequisites, making it incomplete for a mathematical function.

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 100% with parameter description 'The input array.' The tool description adds no additional semantic info beyond what the schema provides, meeting baseline for high 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 'Natural logarithm, element-wise.' clearly indicates the operation and its application to arrays. It effectively distinguishes from siblings like np_log10 and np_sqrt by specifying 'natural logarithm' and 'element-wise'.

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?

No explicit guidance on when to use this tool vs alternatives like np_log10 or np_exp. The description implies it's for element-wise natural log, but lacks context about base or handling of special cases.

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