describe_condition

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

With no annotations, the description carries the full burden. It transparently discloses that the tool returns the docstring and parameter list with types, and explains the two parameter categories (dataset names vs primitive values). It does not mention any side effects or permissions, but for a read-only describe tool, the key behavioral traits are covered.

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 concise with three short sentences. The first sentence states the action, the second describes the return, and the third adds context about parameter types. No extraneous information, and key points are front-loaded.

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 simplicity (one parameter, output schema exists), the description covers the return structure and parameter types adequately. It lacks mention of error handling or what happens if the condition name is invalid, but overall provides sufficient context for an agent to use the tool correctly.

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?

There is only one input parameter ('name'), and the schema description coverage is 0%. The description does not explain what values 'name' should take (e.g., condition names from 'list_conditions'), nor does it provide format or examples. Instead, it elaborates on the parameter types inside the condition itself (dataset vs primitive), which pertains to the output rather than the input semantics.

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: 'Describe the parameters of a ProSuite quality condition.' It specifies what is returned (docstring and parameter list with types) and distinguishes its focus on condition parameters from sibling tools like 'describe_spec' (which likely describes specs) and 'run_verification' (which runs verification). The description also adds detail about dataset vs primitive parameters, making the purpose very clear.

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 provides implicit usage guidance by explaining that dataset parameters must match names in a list passed to 'run_verification', suggesting this tool is used to inspect conditions before verification. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or when-not-to-use scenarios.

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