put-models-training-images-by-model-id-and-training-image-id

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Replace' implies a mutation, the description doesn't specify whether this operation overwrites existing data, requires specific permissions, has side effects, or returns any output. For a mutation tool with zero annotation coverage, this lack of behavioral context is a significant gap.

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, direct sentence with no wasted words. It front-loads the core action and resources, making it efficient and easy to parse. Every part of the sentence contributes to understanding the tool's purpose.

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?

Given the complexity (8 parameters, mutation operation) and lack of annotations or output schema, the description is insufficient. It doesn't explain what 'Replace' entails, how parameters like 'data', 'assetId', or 'preset' affect the operation, or what happens upon success or failure. For a tool with this level of complexity, more context is needed.

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 description mentions 'trainingImageId' and 'modelId' but doesn't explain their semantics beyond what's in the schema. With high schema description coverage (88%), the schema already documents most parameters well. The description adds no additional meaning about parameter usage, interactions, or constraints, so it meets the baseline for high coverage.

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 clearly states the action ('Replace') and the target resource ('trainingImageId for the given modelId'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'put-models-training-images-pairs-by-model-id' or 'delete-models-training-images-by-model-id-and-training-image-id', which handle similar resources but different operations.

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 description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as whether the model or training image must exist, or compare it to related tools like 'post-models-training-images-by-model-id' (which likely creates training images) or 'delete-models-training-images-by-model-id-and-training-image-id' (which deletes them).

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