Execute Experiment

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

With no annotations, the description carries the full burden and does so thoroughly: it clarifies commands run in a container/workspace, never on the host; non-zero exits are normal results; background=true changes behavior; and timeout bounds prevent hangs. This is rich, honest behavioral context.

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?

Four compact paragraphs, each with a distinct job: core action, usage guidance, return behavior, and background execution. The most important information is front-loaded and every sentence adds useful guidance without redundancy.

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 description covers execution environment, return values, non-zero exit semantics, timeout behavior, and the background workflow. Combined with the 100% schema coverage and the presence of an output schema, an agent has enough context to select and invoke the tool 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?

The input schema already covers 100% of parameters, so the baseline is 3. The description adds value beyond the schema by explaining how background=true should be used (poll get_job_status, fetch get_job_result) and by clarifying that timeout bounds execution. This elevates it above the baseline.

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 a shell command inside a sandbox') and gives concrete examples like installs, builds, scripts, and migrations. It is clear what the tool does, but it does not explicitly distinguish itself from the sibling run_tests, which could overlap in the 'run things in the terminal' space.

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?

Gives explicit when-to-use guidance: 'USE THIS for anything you would otherwise run in the developer's terminal.' It also describes the background workflow with get_job_status and get_job_result. However, it does not state exclusions or directly compare against alternatives like run_tests.

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