metrics_distributions

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the output shape and interpretation well, but it does not explicitly state that this is a read-only query, nor does it mention permissions, data freshness, rate limits, or windowing 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 two compact sentences with no waste. It front-loads what the tool returns and follows with the intended interpretation.

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?

For a simple two-parameter read-style metrics query with a fully described schema, the description is largely complete: it explains both the output and the analytical purpose. It could be stronger by noting the default time window or differentiating from sibling metrics tools, but nothing critical for invocation is missing.

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%, so project_id and minutes are already documented in the schema. The description adds no additional parameter guidance such as default behavior or usage constraints, so the baseline of 3 is appropriate.

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 specific metric produced: a response time distribution histogram with p50, p75, p90, p95, and p99 latencies. It is more specific than a generic metrics tool, though it does not explicitly distinguish itself from sibling tools like metrics_summary, metrics_overview, or metrics_routes.

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 gives a clear intended use case: understanding whether latency is consistent or has outliers and slow queries. However, it does not name alternatives or state when another sibling metrics tool would be more appropriate.

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