training_monitor

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

Annotations already indicate readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the description's addition of 'works for private and public projects' adds minimal extra context. No contradictions or further behavioral details are provided.

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, concise sentence (16 words) that front-loads the key information. Every word contributes to the purpose, with no wasted text.

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?

The description fails to address the tool's complexity: no explanation of return values (no output schema), no prerequisites (e.g., training must be active), and no guidance on the optional parameters that control history and metrics. It is incomplete for an agent to use effectively.

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?

With only 20% schema description coverage, the description does not compensate for the 4 undocumented parameters. It adds no meaning beyond the schema, leaving the agent without guidance on 'project', 'history_last_n', 'include_history', and 'include_metrics'.

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 a specific verb ('report') and resource ('model's training status and progress'), and distinguishes itself from siblings like 'training_start' and 'models_get'. The added note about private/public projects further clarifies its scope.

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 implies usage context (works for private/public projects) but lacks explicit guidance on when to use this tool versus alternatives, such as 'models_get' or 'training_start'. No when-not-to-use or exclusions are provided.

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