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

Annotations only provide readOnlyHint=true. The description adds substantial behavioral context: it calculates multiple outputs (Ei, LAS, PPE), uses validated engine, has two current levels, and influences results from enclosure dimensions. It also notes limited free usage. However, it does not discuss authentication (api_key) or error handling, and output structure is not specified.

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 concise paragraph of about six sentences. It is front-loaded with the main purpose and standard, followed by key technical details. While efficient, it could be slightly more structured (e.g., bullet points) for parsing, but overall it is well-sized and not verbose.

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 tool's complexity (11 parameters, 5 required, no output schema), the description covers the core calculation and usage patterns but lacks details on return format, authentication (api_key), error conditions, and prerequisites. It is sufficient for an expert but incomplete for an AI agent needing full behavioral specification.

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 explains config (set of values), t_arc_s/t_arc_reduzido_s (clearing times), and enclosure dimensions (larg_mm/alt_mm/prof_mm) with defaults. However, required parameters (tensao_kv, ibf_ka, gap_mm, dist_trabalho_mm) are mentioned only in context of voltage range and not individually described, leaving gaps for an AI agent.

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 calculates incident energy (Ei), LAS, and PPE category for arc flash using IEEE 1584:2018/NBR 17227:2025, specifying the voltage range (208 V–15 kV). It distinguishes from siblings implicitly via voltage range and provides technical details, making the purpose unmistakable.

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 gives specific usage guidance on providing two clearing times for inverse-curve devices and explains when a single time suffices. However, it does not explicitly compare to sibling tools; the voltage range and standard used serve as indirect differentiators. It also mentions limited free usage, adding context on constraints.

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