describe_keyword

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

With no annotations, the description carries the full behavioral burden and does so well: it states the data source, exact-name matching including hyphen sensitivity, the meaning of default, and the builder_supported limitation. It also names the correct fallback tool for unsupported keyword shapes.

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 dense but front-loaded: it first states what is listed, then explains matching semantics, defaults, limitations, and the argument format. Every sentence adds operational value without repetition.

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 one required parameter, an output schema, and no annotations, the description supplies all key context an agent needs: data source, exact matching rules, default semantics, supported/unsupported keyword shapes, and the fallback tool. Return-value details are already covered by the output schema.

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 description fully compensates by explaining that name is matched exactly, hyphens matter, and the leading * is optional. It also gives a concrete example such as MAT_JOHNSON_COOK.

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 gives a specific verb and resource: list the cards and fields of an LS-DYNA keyword, including field name, type, column, width, and default. It clearly distinguishes the tool from build_keyword and add_keyword_commands by explaining that it inspects keyword definitions rather than building or adding commands.

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?

It explicitly tells the agent to use add_keyword_commands for keywords with repeating-row cards or file/path fields, which is a clear when-not condition and alternative. It also ties the returned default value to build_keyword behavior, giving useful context for when this lookup is relevant.

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