list_experiments

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

With no annotations, the description is the only source of behavioral information. It implies a read-only operation but omits key behaviors such as pagination (despite page/page_size parameters), ordering, or the response format. The phrase 'all experiments' could mislead users into expecting a single non-paginated response.

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 a single, efficient sentence that conveys the core purpose without fluff. It is appropriately sized for a simple list tool and front-loads the essential action.

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 tool has no output schema and no annotations, so the description should compensate by explaining what the client receives, especially pagination details. It does not mention that results are paginated or that 'all' is delivered across pages, leaving a gap for a complete understanding.

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% for both parameters (page and page_size), so the schema already documents their meaning. The description adds no additional parameter context, which is acceptable given the high coverage.

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 the tool lists all experiments in the organization, with a specific verb ('list') and resource ('experiments'), and adds scope ('in your organization'). It distinguishes itself from sibling list tools by naming the resource type, making its purpose unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives like 'get_experiment' or other list tools. The description does not mention exclusions, prerequisites, or suggest when pagination settings might be needed.

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