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

With no annotations, the description carries the behavioral burden. It clearly discloses what the tool returns, what it deliberately does not return ('no time-series or event data'), and the prerequisite call to list_containers. It could add explicit read-only confirmation or error conditions, but the behavioral contract is clear.

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 core purpose and uses bullets for conditions. Every sentence earns its place: purpose, usage triggers, prerequisite, and boundary of what the tool does not return. No filler.

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?

Despite having no annotations, the description gives a complete operational picture: what the tool reveals, when to use it, what to call first, and what to pair it with for missing data. An output schema exists, so return-value detail is not the description's responsibility.

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 the schema already documents both parameters. The description reinforces that container_id starts with 'trc_' and that list_containers can supply it, but it does not add meaningful semantics beyond the schema.

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 opens with a specific verb and resource: 'Detail view of one container.' It then states exactly what the tool reveals (tracked event names and active connectors), which distinguishes it from data-returning siblings like get_report and get_summary.

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 'USE WHEN' section names concrete trigger scenarios, tells the agent to call list_containers first to get the trc_ ID, and pairs get_container with get_report / get_summary for time-series data. It also tells the agent not to guess event names.

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