colab_sessions

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

With no annotations at all, the description carries the full behavioral burden. It implies a read-only listing of 'active' entities and hints at an auth dependency via the sign-in check, which is useful, but it does not state whether it requires prior authentication, what happens when signed out, or whether the call has any side effects.

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, front-loaded sentences with essentially no filler. The 'Also...' sentence is slightly tangential and could have been merged or dropped, but the whole description is tightly sized for a no-argument listing tool.

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?

The tool is simple: no parameters, an output schema that documents the return shape, and no annotations to reconcile. The description covers purpose and one extra use case, which is close to sufficient, though a caveat about needing Google sign-in or the difference from colab_status would have closed the remaining gap.

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?

The schema takes zero parameters, so there is no parameter semantics for the description to explain. Baseline of 4 applies; nothing is missing or misleading on this dimension.

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?

Specific verb + resource: "List active Colab runtimes (sessions)" clearly states what the tool does and clarifies the ambiguous term 'sessions' as runtimes. However, it never distinguishes itself from close siblings such as colab_status or colab_runtime_info, which an agent could easily confuse it with.

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 second sentence adds a secondary use case (verifying Google sign-in works), which implies when the tool is handy. But there is no explicit when-to-use/when-not guidance and no naming of alternatives among the ~40 Colab siblings, so the agent must infer the boundary itself.

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