wavelet_denoise

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

With no annotations, the description carries the full burden. It does disclose real behavior beyond the schema: detail coefficients are thresholded via pywt.threshold and, when threshold is omitted, the universal threshold sigma*sqrt(2*log(n)) with MAD-estimated sigma is applied. However, it says nothing about the returned object, whether the input is mutated, or how level=None is resolved, so the disclosure is partial.

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?

Two short, front-loaded sentences with no filler; the purpose comes first and the algorithmic detail second. Minor formatting artifacts (double backticks, reST role) add a little noise but no length problem.

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?

A 5-parameter numerical tool with no output schema and no annotations needs the description to cover return shape and parameter semantics; it covers one parameter and no return value. An agent cannot tell what it gets back or what mode/level/wavelet do.

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 0% across 5 parameters, and the description only adds meaning for threshold (its default computation). mode (soft/hard), level, wavelet, and the accepted signal types (array or string) remain undocumented in both schema and description.

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?

"Denoise a signal with wavelet shrinkage" is a specific verb+resource+method, clearly distinct from wavelet_transform and filter_signal. It doesn't explicitly name or contrast with those siblings, but the method is named precisely enough to route correctly.

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?

There is no statement of when to use this versus alternatives such as filter_signal, wavelet_transform, or fft_analysis, nor any prerequisites on signal length or sampling. Usage must be inferred entirely from the tool name.

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