generate_documentation

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 does state the core behavior: generating documentation from an input structure and outputting Markdown or JSON Schema. However, it does not disclose behavior around missing inputs, whether both spec and dataLayer can be provided simultaneously, or any side effects, which leaves meaningful gaps.

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 two short sentences with no filler, and the primary action is front-loaded. The second sentence is largely redundant with the format parameter's enum, but it is still efficient and aids quick comprehension. It could have been condensed into one sentence without losing meaning.

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?

This is a 3-parameter tool with no required fields, no output schema, and no annotations, yet the description does not clarify whether at least one of spec or dataLayer must be provided, what happens if neither is given, or how the two inputs interact. An agent lacks crucial calling constraints and return details beyond the format names.

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 100%, so the schema already documents all three parameters and their descriptions. The tool description only restates the concepts of 'data layer structure' and 'tracking specification' that the schema already covers. It adds no additional meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 action ('Generates documentation'), its input source ('data layer structure or tracking specification'), and its output formats ('Markdown or JSON Schema'). This distinguishes it from sibling tools like validate_data_layer, debug_data_layer, parse_tracking_spec, and generate_code, all of which have different purposes.

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 implies when the tool should be used by naming its purpose and inputs, but it does not explicitly state when to prefer it over alternatives or when not to use it. There is no mention of how it differs from generate_code or that validate/debug tools serve different needs. Usage context is only implied, not specified.

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