add_observations

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

Annotations already convey read/write and idempotency characteristics, and the description adds the constraint that entities must exist. However, it does not describe edge-case behavior (e.g., duplicate observations, missing entities) or error handling.

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 11-word sentence that is direct and free of extraneous detail. It gets straight to the point.

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 the simple one-parameter schema and available annotations, the description covers the core functionality. It could benefit from a note about error handling or idempotency behavior, but the output schema likely fills in return-value details.

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 input schema already describes the parameter shape (list of dicts with entityName and contents). The description adds the semantic requirement that entities must already exist, which is not stated in 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 ('Add') and the resource ('new observations to existing entities in the knowledge graph'), using a specific verb and object. It distinguishes from sibling tools like 'create_entities' (which creates entities) and 'delete_observations' (which removes observations).

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 does not explicitly state when to use this tool versus alternatives. However, the action is clear and the sibling context implies its use for enriching existing entities. It lacks explicit exclusions or alternative recommendations.

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