List all Google Colab jobs with optional status filtering to monitor queued, starting, running, completed, failed, cancelled, or timed-out executions.
List all known jobs, optionally filtered by status (queued/starting/running/completed/failed/cancelled/timeout).
| Name | Required | Description | Default |
|---|---|---|---|
| status | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It clearly describes a read-only listing operation with a filter, but does not disclose output format, ordering, pagination, or side-effect implications. For a list tool, the transparency is adequate but not rich.
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?
One sentence with no fluff. It front-loads the main action ('List all known jobs') and then adds the optional filter condition and valid values, every word earning its place.
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?
For a simple list tool with one optional parameter and no output schema, the description sufficiently covers purpose and filter usage. The only gaps are details about what each job entry looks like and pagination/ordering, but these are not critical for selecting and invoking the tool correctly.
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 coverage is 0% and the schema only defines 'status' as a string with no enum or description. The description fully compensates by listing the allowed values: queued/starting/running/completed/failed/cancelled/timeout, and clarifies that filtering is optional. This gives the agent actionable parameter guidance absent from the 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?
States a specific verb and resource: 'List all known jobs', clearly distinguishing it from sibling tools like colab_get_job which targets a single job. The optional status filter with enumerated values further clarifies the 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 for listing jobs and optionally filtering by status, but it does not explicitly contrast against colab_get_job or colab_cancel_job. The usage context is clear enough for an agent but relies on inference rather than explicit exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.