list_experiments

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

With no annotations provided, the description must convey all behavioral traits. It mentions the mandatory dataset filter and partial matching, but it does not describe return format, error behavior when no filter is supplied, or whether this is a read-only safe operation. This is a significant gap for a tool that may filter results and return potentially large data.

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 efficiently structured: a one-sentence purpose, a constraint line, and an Args list. It is not bloated, though the Args list duplicates the schema's parameter descriptions, which is slightly redundant in an MCP context.

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 that there is no output schema and no annotations, the description is only partially complete. It explains the purpose and parameters well but omits return value behavior, possible errors (e.g., what if no dataset filter is provided), and how this relates to sibling tools. For a simple list tool, it is adequate but not thorough.

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 schema covers all parameters at 100% coverage, establishing a baseline of 3. The description adds the 'mandatory filter' constraint that is not captured in the schema properties, which is useful. However, it also repeats the parameter descriptions verbatim, adding little new meaning beyond the schema.

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 action ('List') and the resource ('LangSmith experiment projects (reference projects)'). It also distinguishes itself from sibling tools like list_projects by specifying 'experiment projects' and the mandatory dataset filtering, making its purpose specific and unique.

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?

It provides clear contextual usage by stating 'Requires either reference_dataset_id or reference_dataset_name', which tells the agent when this tool is applicable. However, it does not explicitly compare against alternatives or state when not to use it, stopping short of a full usage guide.

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