design_layer

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

No annotations exist, so the description carries the disclosure burden. It communicates that the tool is an opt-in retrieval mechanism and enumerates the content of each layer, which is helpful. However, it does not describe return format, pagination, error behavior, or explicitly state that the operation is non-mutating, though the 'pull' wording implies read-only.

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 front-loaded with the main purpose and then packs all six layer definitions into a single, dense sentence. While it is effective and every clause adds value, the run-on structure with semicolons and dashes reduces scannability; a bulleted list would be clearer.

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 tool with only one parametrized enum, no output schema, and no annotations, the description is remarkably complete. It covers the purpose, lists all layer options with their contents, specifies the prerequisite call (design_core first), and discloses the opt-in feature (features.rag). There are no significant missing details for the agent to invoke it 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 single parameter layer has 100% schema coverage and an enum, but the schema description is terse ('which layer to load'). The tool description adds substantial meaning by elaborating on each enum value with concrete contents (e.g., 'donts (the vibecoded-tells catalogue...)' and 'scaffolds (occupancy-correct section scaffolds...)'), going well beyond the 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 specifies a concrete action ('Pull ONE deeper design layer on demand, by name') and enumerates each of the six distinct layer options, giving clear resource scope. It also differentiates from the sibling design_core by positioning this as 'deeper' and 'on demand', so the agent knows exactly what this tool does relative to its nearest alternative.

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 provides explicit guidance: 'Call design_core first; pull a layer only when the build needs it.' It also notes the opt-in gating ('features.rag') and points to the generate_image tool for image generation, which gives the agent contextual usage direction and a cross-tool reference.

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