run_cells

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

With no annotations, the description carries the full burden and does substantial work: per-cell blocking, background/polling pattern, and the important caveat that Colab cannot be interrupted through this bridge so cancel only stops scheduling subsequent cells. It omits error behavior despite stop_on_error defaulting to true, and says nothing about output truncation.

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?

Front-loaded with the selection modes, then operational caveats, in three tight sentences with no filler. The warning sentence is dense but every clause (blocking, background, interruption limit) earns 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?

An output schema exists so return values need not be described, and the runtime/blocking semantics are well covered. However, for a six-parameter execution tool the silence on stop_on_error and output size limits, plus no mention of connection prerequisites, leaves 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 description coverage is 0%, so the description must compensate for six undocumented parameters. It explains cell_ids, start_index/end_index (notably "end exclusive") and background, but leaves stop_on_error and max_output_chars entirely undefined in both schema and description — two of six parameters unexplained.

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 ("Run code cells") plus the three selection modes (id list, index range, all), which clearly separates it from run_notebook and run_code by granularity. It does not explicitly name those siblings, so differentiation is inferred rather than asserted.

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 gives strong operational guidance (use background=True plus job_status polling for runs over a minute) but never states when to pick this over run_notebook or run_code, nor the prerequisite of an open Colab connection. Usage context for tool selection is implied by the word "cells" alone.

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