training_monitor

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

With no annotations, the description must disclose behavioral traits. It only states the tool 'reports' status, implying a read operation, and adds a scope note. Missing details include whether it is destructive, authentication requirements, rate limits, behavior on missing models, or return format. The description is insufficient for a tool that likely has complex monitoring behavior.

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 sentence with no unnecessary words, achieving high conciseness. It front-loads the main action ('report a model's training status'). However, it could be slightly more informative without sacrificing brevity.

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 absence of output schema, annotations, and schema descriptions, the description is too minimal. It does not cover return values, error conditions, prerequisites (e.g., training must be running), or pagination. For a monitoring tool with siblings, the description is incomplete for correct invocation.

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%, but the description does not explain any parameters. The required parameter 'model' and optional 'project' are not described; their meaning, format, or constraints are absent. The description adds no semantic value beyond the raw schema, failing to compensate for the low 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 tool reports a model's training status and progress, with a verb ('report') and resource ('model's training status'). It mentions it works for private and public projects. However, it does not explicitly differentiate from siblings like models_get or training_start, though the purpose is distinguishable.

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 explicit guidance on when to use this tool versus alternatives. It only mentions the tool works for private and public projects but does not specify prerequisites, when not to use it, or how it complements sibling tools like training_start or models_get.

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