aurora_findings

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

With no annotations available, the description carries the full transparency burden. It clearly discloses what the returned findings contain and that they are 'verified,' so the agent knows this is an enumeration/read operation rather than a mutation. It does not mention ordering, default limit, or empty-result behavior, but the core behavior is well described.

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 compact yet information-dense: two sentences covering purpose, output shape, filtering, sequencing, and usage guidance. It front-loads the core action and does not waste words.

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 listing tool with no output schema, the description provides strong context: what to do first, what results contain, how to filter, and how to follow up via aurora_explain. It lacks explicit mention of limit behavior and result ordering, but otherwise the agent has enough to invoke 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?

The input schema has 0% description coverage, so the description must compensate. It defines path as 'an Aurora run or bundle,' method as 'statistical method,' and severity with its allowed values ('crit/warn/info'). It does not explain the limit parameter, but the name and schema constraints make it reasonably inferable.

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 starts with the specific verb 'List' and identifies the exact resource: 'verified findings from an Aurora run or bundle.' It enumerates the key output attributes (severity, method, threshold, citation, claim_id), which makes the tool's purpose unmistakable and distinguishes it from siblings like aurora_explain and aurora_analyze.

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 explicitly tells the agent when to use this tool: 'Use after aurora_analyze to enumerate what was actually found.' It also gives a concrete behavioral directive—'quote findings from here instead of paraphrasing from memory'—and points to aurora_explain for evidence drill-down, effectively routing between alternatives.

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