generate_envelope_report

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

Without annotations, the description carries the full burden and does so thoroughly. It discloses that the tool writes a file to reports/, depends on prior load_signal(), uses metadata for sampling rate, reads optional bearing_freqs from _metadata.json, rejects rather than clamps filter_high above Nyquist, and returns a dictionary without HTML content. It also lists exceptions and notes ctx is unused.

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 long but every sentence earns its place. It front-loads the core purpose in the first line, then progressively provides necessary detail on prerequisites, parameters, returns, and exceptions. The example is compact and illustrative. There is no redundant filler.

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?

The description covers prerequisites, side effects, return value format, error conditions, parameter defaults, and edge cases. Even though an output schema exists, it goes beyond that by explaining the dictionary structure. Given the tool's complexity (6 params, file output, dependencies), this is a complete and self-contained description.

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%, but the Args section explains all six parameters with meanings, defaults, and constraints. For example, filter_high: 'Default (None) adapts to the signal: min(5000, Nyquist-1). An explicit value above Nyquist is rejected, never clamped.' The example also demonstrates bearing_freqs structure, fully compensating for the lack of schema descriptions.

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 opens with a clear, specific statement: 'Generate professional envelope analysis report (HTML) for a stored signal.' It identifies the resource (envelope analysis report), format (HTML), and context (stored signal). This distinguishes it from sibling tools like generate_fft_report or generate_iso_report, and the phrase 'instead of inline content' further differentiates it from analyze_envelope.

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 clear usage context: it requires the signal to be loaded via load_signal() first, states that it saves to a reports/ directory, and explains how bearing frequencies are handled. It does not explicitly name alternatives or exclusion scenarios, but the prerequisites and output format give a solid sense of when to use this tool.

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