Read one brand analysis run

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

Annotations cover read-only and open-world, so the safety bar is lower. The description adds real behavioral context the annotations cannot: gaps is empty and sentiment is null until status becomes ready, and error is set on failure. That directly shapes how an agent interprets results, though it doesn't discuss rate limits or pagination.

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 tight sentences, front-loaded with what the run contains and followed by the calling condition. Every clause carries information; nothing is padded.

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 an output schema present, the description needn't enumerate return fields, yet it still previews the key ones (gaps, evidence, sentiment) and warns about their pre-ready states. Nothing needed to invoke or interpret the call correctly 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?

There is a single runId parameter at 100% schema description coverage, and the schema already explains it comes from create_brand_analysis_run. The description adds no further parameter detail, so the baseline 3 applies.

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 names the specific resource (one brand analysis run) and enumerates its contents: gaps, ranking evidence per gap, and sentiment. This clearly distinguishes it from the sibling create_brand_analysis_run, which produces rather than reads a run.

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 explicit sequencing — 'Call it after create_brand_analysis_run until status is ready' — which tells the agent exactly when this tool is the right call. It stops short of naming alternative retrieval tools or when not to use it, but the polling condition is a clear usage context.

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