update_examples

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

With no annotations, the description carries the transparency burden. It clearly discloses that the tool is 'documentation-only', indicating it has no side effects and does not modify data. However, it does not elaborate on what the documentation will contain or how it is delivered.

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 two sentences with no redundant words. The first sentence states the trigger, the second clarifies the tool's nature. Every word contributes to understanding.

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 simple documentation-only tool with no parameters and no output schema, the description adequately covers purpose and behavioral nature. It could specify more about the documentation content, but it is sufficient for an agent to decide when to invoke it.

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 tool has zero parameters, so the baseline for this dimension is 4. The description adds no parameter information, but none is needed since the input schema is empty.

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's purpose: to help the agent understand how to update dataset examples in LangSmith. It uses specific language ('understand how to update dataset examples') and distinguishes this documentation tool from sibling tools that actually perform operations like list_examples or read_example.

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 explicitly specifies when to use the tool ('Call this tool when you need to understand how to update dataset examples'). The phrase 'documentation-only' provides an implicit exclusion (do not use for actual updates), but it does not name alternative tools or provide explicit when-not guidance.

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