stream_status

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

No annotations are provided, so the description carries the behavioral disclosure burden. It implies a read-only status check by listing running state, errors, statistics, and samples, but it does not explicitly state non-mutation, blocking behavior, permissions, or sample recency.

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 a single compact sentence with no filler, and it front-loads the most important status fields. The fragment style is terse but efficient.

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?

With no output schema and no annotations, the description is the only source of return information. It provides useful high-level categories but omits return structure, units, sample count or recency, and statistics names, leaving the agent without a precise return contract.

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?

The tool has zero input parameters, so the baseline is 4. The description does not need to add parameter semantics beyond what the empty schema already conveys.

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 identifies the stream status resource and enumerates returned content: running state, error, live statistics, and recent samples. The purpose is clear, though it does not explicitly distinguish itself from sibling tools such as stream_samples or stream_start/stop.

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?

There is no explicit guidance on when to use this tool, when not to use it, or which sibling to choose instead. An agent can infer it is for checking stream state, but tool selection among stream_status and stream_samples is left to inference.

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