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

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, covering basic safety. The description adds valuable context by specifying that the tool compares metrics against 'AWS public benchmarks and CVE-linked hardware risks' and returns 'a risk assessment with potential root causes'. This goes beyond annotations to explain the underlying behavior.

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 three focused sentences plus keywords. It front-loads the core purpose, then explains input/output, then lists use cases. Every sentence adds value without redundancy. The keyword line aids discoverability without bloating the narrative.

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 low schema coverage and the presence of an output schema, the description could be more complete. It explains what the tool does and its use cases but does not describe the output format (risk assessment) in sufficient detail. It also omits prerequisites or limitations. However, for a read-only tool with clear purpose, it is largely 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?

Schema description coverage is only 20% (only the 'async' parameter has a description). The tool description partially compensates for 'metricType' by listing example values (CPU, latency, memory) and for 'observedValue' by giving examples (CPU utilization, request latency). However, it does not describe 'region', 'instanceType', or the role of 'async', leaving significant gaps for a tool with 5 parameters.

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 action: 'identify anomalous cloud metrics (CPU, latency, memory)' by comparing against 'AWS public benchmarks and CVE-linked hardware risks'. This specific verb and resource set it apart from sibling tools like observability_log_pattern_miner, which focuses on log patterns. The mention of concrete benchmarks and CVEs provides a unique value proposition.

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 says 'Ideal for performance troubleshooting, security hardening, and capacity planning', which gives context but does not explicitly state when to use this tool versus alternatives. There is no mention of when not to use it or which sibling tools serve similar purposes. The guidance is implied rather than explicit.

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