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

The annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered structurally. The description adds useful context beyond annotations by framing it as live production observability and by naming the return categories: aggregated counters, channel breakdowns, latency percentiles, and recent event logs. It still does not mention rate limits, auth requirements, or exact data-freshness semantics.

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 front-loaded with the action and metric scope, and the return-value sentence is relevant. The long parenthetical channel list is somewhat list-heavy, but it supports the sourceChannel field and does not obscure the main purpose.

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?

There is no output schema, but the description names the return categories and the production-monitoring purpose, which is enough for an agent to understand what to expect. It could still clarify freshness, pagination, or output shape details, but it is largely complete for a read-only query tool.

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 coverage is 100%, and the schema already documents limit, eventType, windowHours, and sourceChannel with defaults, max values, enums, and examples. The description echoes the channel list and event-stream concept but does not add syntax or filtering behavior beyond what the schema provides, 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 uses the specific verb 'Query' and enumerates the telemetry resources it covers, such as traffic, attribution, MCP tool calls, OAuth funnel, geography, and live events. It clearly separates this from account, billing, posts, and messaging siblings by domain, though it does not explicitly distinguish itself from the generic analytics_query sibling.

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 says to use this read-only observability tool to monitor how developers and AI agents discover and invoke Nuntior in production, which gives a clear usage context. It does not name exclusions or route the agent to alternatives such as analytics_query when a broader or different analytics scope is needed.

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