connect_catalog

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently reveals a significant side effect: on connection, an MCP workflow and execution are automatically created, and the workflow type is created if absent. It also explains the auto-detection behavior for schemas. It does not mention authentication, error handling, or failure modes, but the disclosed side effects are critical and well-covered.

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 well-structured and front-loaded: the first sentence states the purpose and prerequisite, followed by a brief side-effect note, then Args, Returns, and Examples. Every section earns its place, and there is no verbose filler. Despite being detailed, it remains concise and scannable.

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 tool has 4 parameters, no annotations, and no structured output schema, the description is remarkably complete. It covers purpose, prerequisite, side effects, parameter semantics, return format (JSON fields listed), and two distinct examples. There is nothing critical missing for an agent to select and invoke this tool correctly.

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 has zero description coverage, but the Args section in the description thoroughly explains each parameter with types, examples, and default behavior. For instance, it clarifies that hostname expects a server hostname with examples, catalog_id is a number, domain_schema is auto-detected if omitted, and default_schema has specific fallback logic. This fully compensates for the schema's lack of descriptions.

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: 'Connect to an existing DerivaML catalog.' It specifies the action (connect) and resource (DerivaML catalog), and differentiates from siblings like create_catalog by emphasizing 'existing' and the prerequisite 'Must be called before using other tools.' This gives a specific, unambiguous purpose.

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 explicitly states when to use the tool: 'Must be called before using other tools.' It also provides detailed guidance on when to provide domain_schema and default_schema, including auto-detection logic. However, it does not explicitly name alternatives or when-not-to-use cases beyond the prerequisite, so it just misses a 5.

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