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get-models-by-model-id

Retrieve training status and progress details for a specific AI model using its model ID.

Instructions

Get the details of the given modelId, including its training status and training progress if available

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originalAssetsNoIf set to true, returns the original asset without transformation
modelIdYesThe model's `modelId` to retrieve
Behavior2/5

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

With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions the tool retrieves details including training status/progress 'if available', hinting at conditional data, but lacks crucial context like authentication needs, rate limits, error handling, or response format. This is inadequate for a read operation with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, though it could be slightly more structured by separating purpose from conditional details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read tool with no annotations and no output schema, the description is incomplete. It lacks information on response format (e.g., JSON structure), error cases (e.g., invalid modelId), and operational constraints (e.g., access permissions). The mention of 'if available' for training data is helpful but insufficient for full context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents both parameters. The description adds no parameter-specific information beyond implying 'modelId' is required (already in schema). It doesn't explain the purpose of 'originalAssets' or provide examples, so baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('details of the given modelId'), specifying what information is retrieved (training status and progress). It distinguishes from siblings like 'get-models' (list) and 'get-models-description-by-model-id' (specific field), but doesn't explicitly mention these alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives is provided. The description implies it's for retrieving details of a specific model, but doesn't compare it to siblings like 'get-models' (list all) or 'get-models-description-by-model-id' (partial info), leaving usage context unclear.

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

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