create_pyspark_notebook

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

With no annotations, the description must explain behavior itself, and it does state that a notebook is created and that the return value is either a notebook ID or an error message. However, it does not disclose permission requirements, naming rules, overwrite/idempotency behavior, or what creating from a 'template' actually does to the notebook content.

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 compact and front-loaded with the main action, followed by a clearly structured Args/Returns section. The only real issue is the extraneous 'ctx' entry, which makes the structure slightly less reliable despite being concise.

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?

The description covers the basic call contract: what is created, the key parameters, and the return format. But with no annotations, no output schema, and zero parameter descriptions in the schema, it should also cover prerequisites, template behavior differences, and how to choose among the notebook-creation siblings; those gaps prevent it from being 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 description coverage is 0%, so the Args block adds genuinely useful meaning: it clarifies that workspace accepts a name or ID and lists the template_type options ('basic', 'etl', 'analytics', 'ml'). However, the description also lists 'ctx' as an argument even though it is not present in the input schema, which is confusing and could lead an agent to pass an invalid parameter; it also omits the default value of template_type.

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 uses a specific action ('Create') with a concrete resource ('new PySpark notebook from a template in a Fabric workspace'), so the core purpose is immediately clear. It does not explicitly distinguish this tool from the overlapping sibling tools create_notebook and create_fabric_notebook, which prevents a perfect score.

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 gives no guidance on when to use this tool versus create_notebook, create_fabric_notebook, or generate_pyspark_code. An agent cannot determine which sibling is the correct choice based on this description alone.

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