Audit Project Code

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

Annotations indicate a safe read operation (readOnlyHint=true, destructiveHint=false). The description adds that audit patterns run locally while fix guidance fetch requires network, and details token limits and max files. This provides useful behavioral context beyond annotations.

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, front-loading the main action and then providing details. While it repeats the category list already in the schema, each sentence serves a purpose and adds clarity. Minor redundancy but overall efficient.

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 tool has no output schema, so the description should compensate. It mentions 'returns file:line locations' but does not detail output structure (e.g., severity, fix recommendations). While comprehensive for intended use, it could be more complete about the return format.

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%, so baseline is 3. The description adds value by explaining category usage (e.g., mobile vs web sets), clarifying the tokens parameter purpose, and noting projectPath defaults. This enhances the agent's understanding beyond the raw 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 scans source files for code issues across 18 categories and fetches best-practice fixes. It lists categories and provides specific use-case scenarios, distinguishing it from siblings like gt_auto_scan or gt_batch_resolve.

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 provides explicit guidance on when to use 'all' categories, and gives specific category sets for mobile vs web apps. It also mentions a common failure mode (GitHub token requirement) and how to address it, though it does not explicitly exclude alternative tools.

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