get_tag

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get detailed information'), which is clear, but lacks details about authentication needs, rate limits, error conditions, or what 'hydrate' entails beyond 'additional details.' For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by context about tags, and then parameter details in a structured 'Args:' section. Every sentence adds value, with no redundancy or fluff, though the parameter explanations could be slightly more detailed.

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 moderate complexity (2 parameters, no annotations, but with an output schema), the description is reasonably complete. It covers the purpose, context, and parameters, and since an output schema exists, it doesn't need to explain return values. However, it could benefit from more behavioral details given the lack of annotations.

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 schema description coverage is 0%, so the description must compensate. It adds meaningful context for both parameters: 'tag_name_or_id' is explained as 'The name or ID of the tag to retrieve,' and 'hydrate' as 'Whether to hydrate the response with additional details.' This clarifies their purposes beyond the schema's basic types, though it doesn't specify what 'additional details' include or provide examples.

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's purpose: 'Get detailed information about a specific tag.' It specifies the verb ('Get') and resource ('tag'), and provides context about what tags are in ZenML. However, it doesn't explicitly differentiate from sibling tools like 'list_tags' beyond the singular vs. plural distinction.

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 usage context by explaining what tags are ('cross-cutting metadata labels for discovery') and that 'Many ZenML entities can be tagged,' suggesting when tags might be relevant. However, it doesn't explicitly state when to use this tool versus alternatives like 'list_tags' or other entity-specific getters, nor does it mention any prerequisites or exclusions.

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