get_inferred_rules

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

No annotations present, so description fully covers behavior: declares read-only, no side effects, returns JSON or error if no rules generated. Discloses error condition and parameter filter.

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 sentences, front-loaded with primary purpose. Every sentence adds value: purpose, safety, return format, parameter usage, and sibling alternatives. No wasted words.

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?

Despite no output schema and low schema coverage, description provides return format (JSON with rules including category, pattern, confidence), error case, parameter details, and sibling links. Completely adequate for the tool's complexity.

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 0%, but description lists all valid category values (spacing, colors, typography, borderRadius, naming, components) and explains that omitting returns all. Adds meaning beyond the empty 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 getting design rules inferred from codebase patterns, including the return format (JSON with list of rules) and distinguishes from siblings (get_token, get_conflicts). It uses specific verb+resource ('Get the design rules') with clear scope.

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?

Explicitly states when to use (understand implicit conventions) and when not to (for explicit tokens use get_token, for conflicts use get_conflicts). Also explains parameter behavior: omit for all, pass category to filter.

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