explain_failure

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

No annotations are present, so the description bears full responsibility for behavioral disclosure. It mentions heuristic classification and recommendations but does not describe any side effects, authorization needs, rate limits, or what happens with invalid input. The brief description leaves significant behavioral ambiguity.

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 a single, concise sentence that conveys the purpose and input requirement without redundancy. Every word serves a purpose, making it highly efficient.

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?

While the input schema is fully described, the tool has no output schema, and the description lacks details about the output format or structure. The mention of 'heuristic classification and actionable recommendations' is vague, leaving the agent uncertain about what the tool returns.

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 100% description coverage, detailing all nested properties. The description adds meaning by specifying that the runResult parameter should be the structured result from run_spec, which contextualizes the parameter beyond the schema.

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 analyzes test run results to explain failures with heuristic classification and actionable recommendations. It specifies the input source as 'the structured result from run_spec,' which differentiates it from sibling tools like generate_spec, inspect_server, and run_spec.

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 implicitly guides usage by requiring the structured result from run_spec, indicating it should be used after a run_spec call. However, it does not explicitly state when not to use it or provide alternative tools for similar purposes.

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