frontend_validateAll

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

With no annotations provided, the description carries full burden. It details the categories of violations (critical and warnings) and their implications (e.g., 'would block writes'). This gives a good behavioral overview, though it does not specify output format or side effects beyond being a scan.

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 well-structured with a clear intro, bullet points for violation types, and a usage note. It is informative without being verbose, though it could tighten slightly while retaining key details.

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 description explains what violations are detected but does not describe the output format or how results are returned (e.g., list of issues, severity levels). Given no output schema, this omission reduces completeness for an agent needing to handle results.

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%, but the description adds value by explaining the nature of violations and hinting at default paths (packages/nextjs). It connects parameters to real-world scenarios (e.g., includeWarnings controlling warning display), which aids parameter understanding.

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 scans the entire frontend for critical rule violations, with specific examples of what it checks. This distinguishes it from siblings like frontend_lintDesign which focuses on design linting, and other tools that handle accounts, stacks, or addresses.

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 explicitly advises to use this tool before deployment or to find existing issues, providing clear context for when to use it. However, it does not mention when not to use it or alternative tools, leaving some room for improvement.

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