Retrieve the tail of a submitted GPU job's log by job ID, with an optional character limit, to inspect output and diagnose errors from Kaggle or Colab runs.
Tail of the job log. Mock data are TEST FIXTURES, not a live account.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | ||
| max_chars | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears the full burden. It does disclose two useful traits—output is a truncated tail, and data are mock test fixtures rather than a live account—but says nothing about permissions, behavior when the job is missing or still running, or how max_chars affects results.
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?
Two short sentences, front-loaded with the core action and no filler. It is efficient, though the brevity borders on under-specification rather than being purely economical.
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 are covered, but with zero schema coverage and no annotations the definition leaves the agent without parameter meanings, error behavior, or selection guidance. Too thin for a tool with a required identifier parameter.
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%, so neither job_id nor max_chars is documented anywhere. The word "tail" vaguely implies that max_chars truncates output, but no units, defaults, or identifier format are given in the description.
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?
"Tail of the job log" names a specific resource and operation, enough for an agent to know this returns recent log output. It does not, however, distinguish itself from the near-identical sibling l2kc_get_job_logs or from gpu_get_job_status.
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?
There is no statement of when to call this versus gpu_get_job_status, gpu_list_jobs, or the l2kc equivalent. The only supplementary sentence is a data-provenance warning, not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.