generate_data_dictionary

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

With no annotations, the description must carry the behavioral burden. It discloses that output_path optionally saves the Markdown (a file-write side effect) and describes the return payload, but says nothing about permissions, cost, or whether the operation touches the model. Adequate but thin for a tool with zero annotation coverage.

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?

Front-loaded one-line purpose followed by scannable trigger bullets and Args/Returns sections. The Returns block slightly duplicates the output schema, but overall it is efficient and well-organized.

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 3-parameter documentation generator with an output schema present, the description covers purpose, triggers, parameters, and return shape. Nothing essential to a correct invocation is missing, though the inspector parameter's nature remains unspecified.

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 description must compensate, and it documents all three parameters: pbip_path as 'Path to the .pbip directory', output_path as an optional save path, and inspector as an optional model inspector. Only 'inspector' is somewhat circular/tautological, so a 4 rather than 5.

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?

States a specific verb+resource (generate Markdown documentation and Mermaid ER diagram) for a semantic model, and the trigger bullets make the output artifacts concrete. It is clearly distinguishable from siblings like audit_model_and_report or create_report_from_dataset.

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?

Provides an explicit 'Use this tool when the user asks to' list with three concrete trigger scenarios (document a dataset, generate a data dictionary, create a Mermaid ER diagram). It gives clear positive context but no when-not conditions or named alternatives.

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