colab_restart_kernel

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

With no annotations, the description carries the full burden and does disclose the key destructive effect (all Python variables cleared) alongside what is preserved (VM and files) — exactly the trade-off an agent needs. It stops short of saying whether in-flight execution/jobs are interrupted or what auth/session ownership is required.

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 front-loaded sentence with the verb first and the destructive/preserving consequences trailing. Nothing redundant; every clause adds information.

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 no prose, and the core side effects are covered. Still, for a mutation-style tool with zero annotation coverage, the unstated behavior of the null-defaulted session parameter and whether restart interrupts running cells leaves an agent with real gaps.

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 single 'session' parameter is optional with a null default, so the schema explains nothing. The description refers to 'a session' but never says which session is targeted when the argument is omitted, nor what the session identifier format is, leaving the only parameter ambiguous.

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 (restart) and resource (Jupyter kernel of a session), and immediately scopes it against the obvious sibling behavior: variables are cleared but the VM and files persist, which separates it from colab_stop (which would kill the runtime). An agent can pick this over colab_stop, colab_new, or colab_exec without opening any schema.

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 only implied: by saying variables are cleared while files persist, it hints at 'use when you want a clean Python state without losing work.' It never names an alternative tool or an explicit when-not condition (e.g., 'to free the VM entirely, use colab_stop'), so the routing decision is left partly to inference.

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