Audit Project Code

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

Annotations already declare readOnlyHint=true and destructiveHint=false; the description adds that audit patterns run locally and only fix guidance fetch requires network, plus troubleshooting for token limits. No contradiction.

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-organized with a clear first sentence, a bullet-like list of categories, usage patterns, and a troubleshooting note. Though somewhat lengthy, each part adds value and there is no redundancy.

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 tool's complexity (18 categories, network dependency, multiple parameters), the description covers purpose, categories, usage patterns, return format, and a potential failure mode. No output schema exists, so return value explanation is adequate.

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 baseline 3. The description enriches by listing all categories, explaining the default 'all', providing concrete usage examples for categories, and clarifying the purpose of tokens and maxFiles beyond the schema definitions.

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 source files for code issues across 18 categories and fetches live best-practice fixes, returning file:line locations. It distinguishes from siblings by emphasizing the combination of scanning and fetching fixes.

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?

Provides explicit use cases: 'for broad questions use categories: ["all"]' and specific category sets for mobile vs web apps. Also notes potential failure of doc fetches and need for GT_GITHUB_TOKEN. However, it doesn't contrast with sibling tools like gt_auto_scan or gt_best_practices.

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