Summarize a LoRA training job's loss curve with first, last, and minimum values, a smoothed trend, and evenly spaced points to monitor run progress.
Loss curve summary: first/last/min values, a smoothed trend, and evenly spaced points.
| Name | Required | Description | Default |
|---|---|---|---|
| job | Yes | ||
| key | No | loss | |
| max_points | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds useful output context (first/last/min, smoothed trend, evenly spaced points) but does not disclose error behavior, pagination, or whether the job must exist.
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 filler. Every phrase contributes to the output summary being described.
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?
An output schema exists, so return values need not be fully explained, and annotations cover safety. Still, the description does not clarify the required job identifier or what 'key' controls, which matters 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% and the description does not explain the required 'job' parameter or the 'key' and 'max_points' parameters. 'Evenly spaced points' vaguely gestures at max_points, but the core parameter semantics are left to the bare schema.
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 names a specific resource and output type: a loss curve summary with first/last/min values, trend, and sampled points. It is clear what the tool returns, but it does not distinguish itself from siblings such as get_job_log or list_job_outputs.
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?
Usage is implied by the phrase 'Loss curve summary' – an agent can infer it is used when a compact loss overview is needed. However, there is no explicit when-to-use guidance, no exclusions, and no mention of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.