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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), lowering the bar. The description adds that the samples 'compile with 0 errors', a useful quality guarantee, but says nothing about how many examples are returned, their format, or ordering.

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?

Two compact sentences, front-loaded with what is returned and then how to use it. Every clause earns its place, including the parenthetical taxonomy of example types.

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?

With no parameters, no output schema, and read-only annotations, the description carries most of the burden and does describe the shape of the returned content. It stops short of stating count, format, or whether the examples are static, but is otherwise sufficient to call the 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 tool takes no parameters, so there is no schema to clarify and the baseline is 4. Nothing in the description conflicts with the empty input schema.

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 states a specific verb ('Return') and resource ('reviewed PBL showcase posts') and enumerates the four example types it yields, making the tool's output concrete. It is distinguishable from sibling blueprint tools like picorn_blueprint_compile, though it never names an alternative explicitly.

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?

It gives clear intended usage ('Use them to learn proven structure, spacing and effect choices') and a do/don't boundary ('write new copy, colours and fonts from the brief instead of reusing theirs'). It lacks any explicit comparison to sibling tools such as blueprint_spec or blueprint_compile, so routing is inferred rather than stated.

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