get_special_results

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that this is a 'post-analysis' results query, which hints that an analysis must have been run, and it shows the result kinds available. However, it does not disclose behaviors such as which parameter combinations are required per kind beyond the inline notes, or what happens when no results exist. This is acceptable but not exceptional given the annotation coverage.

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 core purpose is stated in one front-loaded sentence, followed by a well-organized Args block. The bilingual formatting adds length but also disambiguates technical terms. It is somewhat verbose with 11 parameters, yet each line earns its place by adding needed meaning. It could be tightened slightly but remains well structured.

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?

For a high-complexity tool with 11 parameters, no schema descriptions, and no output schema, the description is notably complete on the input side: it covers parameter meanings, required combinations, and default behavior via defaults. Missing pieces include the output shape and the precise semantics of generic flags like result_kind, envelop_type, and increment_type, but the description still gives an agent enough to call the tool correctly for most cases.

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?

The input schema has zero descriptions, so the description carries the full burden, and it delivers. It explains every parameter, provides allowed values for the 'kind' parameter, and explicitly notes which additional parameters are required for each result kind (e.g., '需 mode', '需 node_id + case_name'). This is substantially more informative than the bare schema.

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 specific verb and resource: 'Get special post-analysis results', and immediately distinguishes itself from the sibling get_analysis_results by saying it covers results 'beyond the basic deformation/force/stress/reaction'. It also enumerates the exact result kinds, so an agent can tell exactly what this tool does and what it is not for.

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 when to use this tool: when special post-analysis results are needed, as opposed to the basic results covered by get_analysis_results. It explicitly names that sibling tool, which provides useful routing context. It does not go as far as stating explicit exclusion conditions ('do not use for X'), but the contrast with the sibling is clear enough.

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