Evaluate Design

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

Annotations already declare the safety profile: non-destructive, not read-only, not idempotent, closed-world. The description adds valuable behavior beyond that by explaining score ranges, per-axis ratings, advisory integrity findings, and that a 'selection' finding names the offending pattern and drives reselection upstream. It does not clarify why the tool is not read-only or whether any evaluation state is persisted, leaving a minor gap.

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 tightly written sentences with no wasted clauses. The purpose and output shape are front-loaded, followed by the required inputs and upstream tool relationships. Every sentence earns its place.

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?

The tool has an output schema, so the description need not fully restate return values, and it still summarizes the important output categories. Annotations cover the safety profile, and the description explains upstream input sources and downstream reselection behavior. For this complexity level, the definition is complete enough for correct invocation.

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 design_json, requirements, and the optional analysis payload. The description adds useful provenance by saying design_json should come from generate_design or select_design_patterns and that analysis can be a prior analyze_design payload. That meaningfully supplements the schema, though it does not add format or validation detail beyond it.

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 and resource: evaluate a design draft against requirements. It also names the outputs (scores 0-100, per-axis ratings, findings) and distinguishes the special 'selection' finding that drives upstream reselection. An agent can identify this as the scoring/validation step versus generation or selection siblings.

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?

Clearly tells the agent to pass a design returned by generate_design or select_design_patterns, plus requirement text or a prior analyze_design payload. This establishes the upstream/downstream flow. It does not explicitly state when not to use it or name alternative evaluation paths, so it stops short of a 5.

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