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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: the 20-row result cap and the explicit exclusion of full logs and rows, which sets an agent's expectation about output volume.

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 short sentences, zero filler, with the resource and scope front-loaded. Every clause adds information an agent can use.

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?

An output schema exists, so return values need not be re-explained, and annotations cover the safety profile. The remaining gap is the ambiguous optional workspace_id, which the description never addresses.

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 0% across two parameters, so the description must carry parameter meaning and it does not. It says nothing about run_id or the optional workspace_id, including whether workspace scoping is required or how it is resolved.

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?

States a specific verb and resource ('Read the selected run's recorded status') plus the scope of what is returned ('up to 20 output row counts'). It is clear what the tool does, though it doesn't explicitly contrast itself with sibling read tools like get_pipeline or browse_dataset_rows.

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 clause 'No full logs or rows' implicitly steers the agent away from expecting detail and hints that fuller-read siblings exist, but it never names an alternative or states a when-to-use condition. Usage is implied rather than specified.

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