get_help_center_structure

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

Discloses that including article counts can be slower on large Help Centers, which is useful beyond the readOnlyHint annotation. Provides this behavioral trade-off without contradicting annotations.

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?

Single, succinct sentence that front-loads the purpose and adds a performance note. No redundant phrases or verbosity.

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?

Adequate for a read-only, single-parameter tool. No output schema, but the description implies a tree structure; missing explicit return format is a minor gap.

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 covers the parameter fully, but the description adds context on performance impact and default behavior, which is valuable beyond the schema alone.

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?

Clearly states it retrieves the Help Center's structure as a tree, including categories and sections, with details like article counts and dates. Distinguishes itself from article-specific tools by focusing on the overall structure.

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?

Implies use for assessing content gaps or staleness, which suggests when to use (analysis) versus alternatives like get_article. Lacks explicit exclusions, but the use case is clear.

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