model_impact

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

The readOnlyHint annotation already establishes that this is a safe read operation. The description adds useful scope with 'all transitive upstream and downstream,' but it does not describe output shape, traversal limits, or any caveats.

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 front-loaded sentence with no wasted words. It states the core behavior immediately.

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?

For a simple read-only tool, the description adequately states the returned scope, but it leaves gaps around parameter semantics, output shape, and routing relative to sibling lineage/dependency tools. With no output schema and no parameter documentation, those omissions matter somewhat.

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 one required parameter, model_name, and schema description coverage is 0%, so the description should compensate. It never explains the parameter's expected format or naming conventions, though the parameter name itself is fairly self-explanatory.

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 gives a specific verb and resource: return all transitive upstream and downstream models affected by a change. It is clear what the tool computes, but it does not explicitly distinguish itself from close siblings such as get_model_dependencies or lineage.

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 phrase 'affected by a change' implies impact-analysis usage, but there is no explicit guidance on when to choose this tool over lineage or dependency tools. No exclusions or alternatives are stated.

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