get_metrics_framework

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds return-content transparency by stating it returns structure, when-to-use info, pitfalls, and examples, which is useful beyond the annotations.

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?

Two sentences, front-loaded with the resource list and followed by return contents and usage triggers. No filler or repeated schema information.

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 has 2 optional params fully documented in the schema, no output schema, and annotations covering side effects. The description adds return-value expectations and triggering phrases, making it complete enough for reliable invocation.

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 100% — both parameters ('id' and 'search') are already documented in the schema. The description adds no meaningful parameter semantics beyond the framework list, so the baseline score of 3 applies.

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 uses a specific verb ('Get') and names a distinct resource class ('product-metrics framework') with an explicit list of six frameworks. It is immediately distinguishable from sibling knowledge-retrieval tools by its metric/measurement focus.

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?

Provides an explicit trigger condition: use when the user asks 'how should we measure success?' or 'what metrics should we track?'. It does not name when-not-to-use or point to alternatives, but the quoted use cases are clear enough for an agent.

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