summarize-experiment

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

No annotations are provided, so the description carries the full burden. It explains the output components (overview, runs, stats) and sorting behavior, but does not explicitly state that it is a read-only operation or disclose any side effects. Adequate but not fully transparent.

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 sentences, front-loaded with the main purpose, no extraneous information. Every word 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?

Given no output schema, the description provides a high-level overview of the return payload (experiment overview, runs, stats) but lacks specifics about fields in the overview. Still sufficient for an aggregated view tool.

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 100%; the input schema already describes all parameters. The description adds minimal value beyond restating schema details (e.g., default 5, max 20). Baseline 3 is appropriate.

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 explicitly states it provides an aggregated experiment view (overview, topN runs, metric stats) and distinguishes from siblings by noting it replaces multiple round-trips (get-experiment, search-runs, get-best-run).

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 clearly communicates when to use this tool—when an aggregated view is needed—and contrasts with alternative approaches by stating it saves 3-5 round-trips. However, it does not explicitly state when NOT to use it (e.g., if fine-grained filtering is needed).

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