colab_job_logs

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

No annotations are provided, so the description carries the full burden. It only restates the return content (stdout/stderr + state), which the output schema already covers, and says nothing about read-only safety, log truncation beyond 'tail', or permissions.

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 tightly written sentence with the key payload (stdout/stderr) front-loaded and no wasted words. It is appropriately sized, though extremely terse.

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 explained. However, with three parameters at 0% schema coverage and no usage context against many job-related siblings, the description leaves real gaps an agent must guess at.

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 the schema explains none of the three parameters. The description's use of the word 'tail' hints at the tail parameter, but job_id and session remain entirely undocumented in both places.

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 resource (background job's combined stdout/stderr) and what is returned (last tail lines plus state). It is clear about scope, though it does not explicitly distinguish itself from log-related siblings like colab_job_status or colab_log.

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 indication of when to use this tool versus colab_job_status, colab_job_list, or colab_log. The agent must infer from the name alone that this fetches log output for a job that already exists.

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