orm_call

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

No annotations exist, so the description carries the full burden. It discloses result truncation at 20 kB and notes that it bypasses the UI and runs through the session, implying authentication context. It also implies side-effecting operations ('create for test data'), though it does not detail error behavior or potential data integrity impacts.

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 three sentences with no redundancy. It front-loads the core action, then states purpose/usage, then a critical output limit. Every sentence contributes value, making it both concise and easy to scan.

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 generic ORM caller, the description provides essential context: purpose, session/authentication, and a 20 kB truncation limit. It lacks explicit notes on model name validation or method availability, but given the tool's generic nature and the presence of an output schema, it is reasonably 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?

The schema has zero descriptions (0% coverage) and only type/title information. The description gives examples of methods but does not explain the structure or intended use of 'args' and 'kwargs' beyond their schema types, leaving agents to guess that args are positional and kwargs are keyword arguments—an important gap for a generic method caller.

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 states a specific verb ('call') and resource ('model method'), and adds context that it executes server-side through the logged-in session. Concrete examples (search_read, read, name_search, create) clarify the intended usage and clearly distinguish it from the UI manipulation siblings.

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 says to use it to 'prepare or verify data' and 'not to replace the user flow', which provides clear when-to-use guidance relative to UI tools. However, it does not name specific alternative tools or describe scenarios where another tool would be preferred, leaving some inference to the agent.

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