Get Experiment

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

With no annotations present, the description carries the full disclosure burden and meets it by enumerating the returned contents: status, base image, isolation settings, resource limits, command counts, last test summary, change statistics and artifact count. This is unusually transparent for a read tool, effectively previewing the output schema, though it does not address error or edge-case behavior.

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?

The description is organized into three scannable sections — a one-line purpose statement, a 'USE THIS' directive, and a 'RETURNS' list — with the most decision-relevant guidance front-loaded. No sentence is wasted, though the RETURN enumeration is slightly verbose for a tool that already declares an output schema.

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?

For a simple single-parameter read tool, the description covers purpose, usage triggers, and return contents comprehensively, and an output schema is declared so return values are further specified structurally. Nothing an agent needs in order to call it correctly is missing.

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 single parameter experiment_id is 100% covered by the schema description ('The experiment to describe.'), so the schema already carries the meaning. The description adds nothing parameter-specific beyond the schema, holding it at the baseline 3.

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?

The description opens with a specific verb ('Fetch') and resource ('an experiment's full state and a summary of what happened in it'), clearly scoping the tool's function. It is distinguishable from siblings like get_job_status and check_sandbox_runtime by the breadth of state described, though it does not explicitly name a sibling to differentiate against, so it misses full marks.

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 includes an explicit 'USE THIS to re-orient' directive with concrete trigger conditions: after a long gap, or to check sandbox liveness before sending more commands. This gives clear when-to-use context, though it stops short of naming alternatives or stating when NOT to use it.

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