search_experiments

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

The description explains the tool's read-only behavior (consistent with readOnlyHint annotation) and details the filtering and sorting capabilities. It goes beyond annotations by describing parameter format and supported fields, but does not disclose edge cases or default ordering 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 well-structured with a concise purpose statement, bullet-like parameter explanations, and examples. It is front-loaded and every sentence adds value. Minor improvement possible by shortening the examples slightly.

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 search tool with an output schema, the description covers parameter semantics and usage examples. It does not discuss pagination or default result limit behavior, but these are minor omissions. Overall, it provides sufficient context for an AI agent to use 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?

Despite 0% schema description coverage, the description fully explains all three optional parameters: filter_string (with column names and examples), order_by (format and example), and max_results (default value). This compensates entirely for the schema gap and adds meaningful semantics.

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 clearly states 'Search experiments with optional filtering and sorting,' specifying a specific verb and resource. It distinguishes from sibling tools like search_logged_models and search_runs_by_tags by targeting experiments. The included filter syntax and examples further clarify its purpose.

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 provides examples and explains filter syntax, which implies when to use. However, it does not explicitly state when not to use this tool or mention alternatives such as get_experiments or get_experiment_by_name for simpler queries. The guidance is adequate but not comprehensive.

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