colab_job_status

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

With no annotations, the description carries the full behavioral burden, and it does disclose genuinely useful state-machine information (running, finished with exit code, cancelled, lost). However, it says nothing about whether this is a read-only, non-blocking check or whether it waits, which matters for a status-polling tool.

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?

A single tight sentence with no filler and the core purpose front-loaded. It is a noun phrase rather than a full statement, but nothing in it is wasted.

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 re-explained, and the state enumeration is a useful bonus. Still, with 0% parameter coverage and no usage guidance, the definition leaves real gaps for a tool that must be polled 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 description coverage is 0%, so both parameters are undocumented in the schema. The description implies job_id selects the job but gives no format or origin for it, and the optional 'session' parameter is never mentioned at all.

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 ('a background job') and the operation ('state'), and even enumerates the possible return states. It is clearly distinguishable from write siblings like colab_job_start or colab_job_cancel, though it does not explicitly differentiate from the adjacent colab_job_logs or colab_job_list.

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 guidance on when to call this versus colab_job_logs, colab_job_list, or colab_job_cancel, nor any mention of polling or how to obtain a job_id. The agent must infer usage entirely from the tool name.

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