list_experiment_runs

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

With no annotations supplied, the description carries the full burden, and it only partly does so: it discloses ordering ('start time descending') and that results are summaries. It does not state that the operation is read-only, whether results are paginated or truncated, or any permission requirements.

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 sentences, front-loaded with scope and followed by the ordering guarantee; nothing is wasted. The parenthetical phrasing is slightly informal but functional.

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-value explanation is not required, and the tool is simple with one optional parameter. However, the absence of annotations leaves gaps around read-only behavior, result limits, and paging that the description does not cover.

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 parameter has only a null default, so the description must compensate. It does explain the important semantic that omitting experiment_id returns runs across all experiments, but it never says what format experiment_id takes (identifier vs. name), which is the key remaining ambiguity.

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 names a specific verb (List) and resource (runs for an experiment), and the parenthetical '(or all experiments)' clarifies the scope when no filter is given. It is distinguishable from siblings like list_observations and get_experiment_result, though it never explicitly contrasts itself with them.

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?

There is no explicit when-to-use guidance. The optional parameter implies two modes (single experiment vs. all), but the description does not say when an agent should call this versus get_experiment_result, run_experiment, or list_observations.

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