list_conditions

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

The description effectively communicates the read-only nature of listing conditions and the return format (names and descriptions). It could be slightly more explicit about being non-destructive, but the behavior is clear. No annotations exist, so the description carries the full burden adequately.

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?

Three concise sentences with no wasted words. The purpose is front-loaded, and follow-up actions are efficiently described.

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?

The description is complete given the tool's simplicity (1 optional parameter with default, no required fields, output schema exists). It provides enough context for an AI agent to correctly select and invoke the tool among siblings.

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 only parameter 'search' is explained in the description: it filters by keyword matched against name and description. This adds significant meaning beyond the schema name 'Search' alone, compensating for 0% schema description coverage.

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 lists available ProSuite quality conditions, providing condition names and one-line descriptions. It distinguishes from siblings like describe_condition which provides full parameter details, and run_verification for execution.

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?

Explicitly mentions using the search parameter to filter by keyword, and advises passing a result name to describe_condition for full details before building a run_verification call, guiding proper usage and tool chaining.

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