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

The readOnlyHint annotation already signals a safe read operation, and the description adds that results include examples and counterfactuals. However, it doesn't disclose return shape, size, or ordering. With annotations covering safety, a score of 3 fits: the description adds some meaningful context but not deep behavioral detail.

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?

A single, front-loaded sentence with no filler. Every word earns its place by specifying the resource and two concrete content attributes.

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 parameterless, read-only tool, the description supplies sufficient information to understand what the tool returns. Some extra context about the format or length of the returned principles would round it out, but nothing critical is missing.

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 is empty with 0 parameters, so schema coverage is trivially 100%. The description needs no parameter explanation, and the baseline of 4 applies. It gives no misleading parameter hints.

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 verb+resource ('Get engineering principles') and clarifies what the content includes ('real examples and A/B-style counterfactuals'). While it doesn't explicitly differentiate from siblings like get_antipatterns or get_articles, the resource noun 'engineering principles' is distinct enough.

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?

There is no guidance on when to use this tool vs alternatives. The context signals show no parameters, so its use is simple, but the description gives no conditions, exclusions, or references to sibling tools that might be alternatives for similar lookups.

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