add_observations

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

With no annotations, the description only indicates mutation (add). It does not disclose error handling (e.g., missing entity), idempotency, or safety traits. The output schema exists but isn't shown, so behavioral gaps remain.

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?

Two concise sentences: first states purpose, second details parameter structure. No unnecessary words, efficient front-loading of key info.

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 output schema exists, return info is covered elsewhere. However, the description lacks usage guidelines and behavioral details, which are needed for a tool with 0% schema coverage and no annotations. It covers the basics but is not fully complete.

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 coverage is 0%, so the description adds significant value by specifying that each dict must have entityName (str) and contents (list[str]), which is missing from the schema. This provides critical structure for the agent.

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 resource (observations to existing entities), and specifies required fields in each dict. However, it does not explicitly distinguish from sibling tools like create_entities or delete_observations, though the purpose is evident.

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 on when to use vs alternatives, no prerequisites mentioned (e.g., entities must exist), and no when-not-to-use info. The description implies usage but lacks explicit context for an agent to decide between this and sibling tools.

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