correlate_deploy_with_errors

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

Annotations already indicate readOnlyHint=true, and the description adds substantial behavioral detail: it 'compares error rate and p99 latency before vs. after', 'pulls matching ERROR log samples', and 'returns a verdict with a confidence level.' This goes beyond the annotations and helps the agent understand what the tool actually does internally and what kind of output to expect.

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?

Every sentence earns its place: purpose, behavior, and usage guidance are all compressed into three short paragraphs. It is front-loaded with the main purpose and avoids irrelevant details. The structure is clean and 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?

Given an output schema exists (which covers return structure), the description is complete enough. It covers the analysis logic, the window concept, and when to use the tool. The complexity of a multi-step correlation is well summarized, and the agent has enough context 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?

Schema description coverage is 0%, so the description must compensate. It refers to 'the window', which implicitly maps to the lookback_minutes parameter, and the schema shows a required 'service'. However, it does not explicitly explain the parameter names, types, or constraints beyond the vague 'window' mention. The parameter names are self-explanatory but the description adds minimal semantic value.

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: 'Find whether a recent deploy explains a service's current errors.' The verb 'find' and resource 'recent deploy vs. service errors' are specific. It distinguishes itself from siblings like get_deploys and query_logs by focusing on correlation and before/after arithmetic.

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?

Explicit when-to-use guidance is provided: 'This is the tool to reach for on "why is X broken"' and it contrasts with the alternative chain of get_deploys + get_metrics + query_logs. This gives the agent clear criteria for selecting this tool over siblings.

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