analyze_root_cause

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

Despite readOnlyHint/idempotentHint/destructiveHint covering safety, the description reveals the internal cross-referencing process and defines the output structure with likelihood, confidence, and evidence, plus a confidence threshold interpretation (0.7 high certainty).

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 sentences with a clear progression: what it does, how it works, when to call it. No redundancy or fluff.

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 tool's complexity is moderate; 2 params with rich schema, and the description covers the output structure (since no output schema exists) and usage context. It explains the internal steps and confidence interpretation, making it self-sufficient.

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?

Both parameters are fully described in the input schema with examples, and the description names them implicitly ("service", "symptom"), but adds no new syntax or format details beyond the schema. Schema coverage is 100%.

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 opens with a specific verb "Performs automated root cause correlation" and names the resource ("a service exhibiting a given symptom"). It distinguishes itself from siblings by explicitly labeling itself "the primary reasoning tool" and referencing the preceding data collection tools.

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?

It explicitly instructs to "call it after collecting data with get_recent_deployments, get_service_logs, and get_service_metrics," giving a clear precondition. It positions itself as the analysis step between data gathering and action tools, though it does not list explicit when-not conditions.

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