brand_generate_designmd

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

Without annotations, the description discloses key behaviors: 'Read-only except for writing the two output files' and explains fallback logic between extraction-evidence.json and core-identity.yaml plus tokens.json. It does not detail permissions or error states, but the side-effect is well-described.

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?

Three focused sentences: first defines core function, second clarifies source behavior, third provides usage context. No redundant words, and critical information is front-loaded.

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?

Given the complexity of generating dual files with synthesis, the description covers inputs (params), outputs (file paths and source), preconditions (use after specific extraction tools), fallback, and exclusions. With no output schema, the description adequately notes return value.

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 coverage is 100%, so parameters are already documented. The description adds context: the 'source' default behavior ('prefers extraction evidence when available, otherwise current-brand') and the 'overwrite' behavior ('return existing artifacts without rewriting'). This clarifies decision logic 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 clearly states the tool generates DESIGN.md and design-synthesis.json from the current brand system, enumerates the design signals included, and distinguishes itself from sibling extraction tools by specifying its role as a synthesis step. It also explicitly states what the tool is NOT for.

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?

Explicit guidance is provided: 'Use after brand_extract_site or brand_extract_visual... Use after brand_compile if evidence is unavailable.' It also directs users to alternative tools for other purposes: 'NOT for extracting brand identity — use brand_extract_web or brand_extract_visual first.'

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