design_database

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

No annotations are provided, so the description carries the behavioral transparency burden. It does disclose the produced artifacts (ER diagrams, table definitions, indexes, recommendations), which helps convey a non-mutating design-like output. Still, it does not explicitly state whether the tool has side effects, whether it writes files, or how the result is delivered.

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 compact and front-loaded: it opens with the core action and resource, then lists concrete deliverables, and ends with template context. Every sentence adds useful information with no filler.

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 a simple two-parameter input schema, full schema documentation, and no output schema, the description provides enough context by naming the expected deliverables. It does not describe the response format in detail or edge cases like the 'other' project type, but the tool's scope is modest and the key usage context is present.

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?

Input schema coverage is 100%, with both parameters already described in the schema, so the baseline is 3. The description adds only marginal context by pointing to e-commerce and SaaS templates, which aligns with the project_type enum, but does not substantially enrich understanding of the parameters 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 uses a specific verb-resource pair, 'Design database schema', and enumerates concrete outputs: ER diagrams, table definitions, indexes, and recommendations. This clearly sets it apart from sibling tools like design_architecture and design_api.

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 implies when to use the tool—whenever a database schema needs to be designed—and mentions templates for e-commerce and SaaS as context. However, it does not explicitly state when not to use it or name alternative sibling tools for similar tasks, so guidance is only implicit.

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