compute_fft

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

No annotations are provided, so the description carries full burden. It reveals configurability (window, zero-padding) but does not state side effects, prerequisites, or what happens to source data. The phrase 'last_loaded' is unexplained, and behavioral traits like non-destructive nature are absent.

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 a single sentence, front-loaded with purpose and key features, with zero wasted words. It is appropriately sized for its role.

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 4 parameters with 0% schema coverage, no annotations, and an existing output schema, the description is too sparse. It omits details about source parameter usage, how n_fft affects output, and does not clarify the computation context (e.g., real vs complex). An agent would need additional knowledge to use this 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 0%, so the description must compensate. It adds value for window (lists Hann/Hamming/Blackman) and zero-padding factor, but n_fft and source (which has a default 'last_loaded') are not explained. This provides partial but insufficient compensation.

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 explicitly states 'Windowed FFT with configurable window and zero-padding factor,' clearly identifying the verb (compute FFT) and resource (signal data) with specific configurables. It distinguishes from sibling tools like render_spectrogram and range_doppler_map which are higher-level or different algorithms.

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 implies usage when a plain FFT is needed, but lacks explicit guidance on when to use this tool versus siblings like render_spectrogram or range_doppler_map. No alternatives or when-not-to-use are mentioned.

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