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Audit Project Code

gt_audit
Read-onlyIdempotent

Scan your own source code for issues in 18 categories including security, performance, accessibility, and more, then get live best-practice fixes from official docs with exact file:line locations.

Instructions

Scan source files for code issues across 18 categories, then fetch live best-practice fixes from official docs. Returns file:line locations. Unlike gt_auto_scan (best practices for your dependencies), this audits YOUR OWN source code.

Categories: layout, performance, accessibility, security, react, nextjs, typescript, node, python, vue, svelte, angular, testing, mobile, api, css, seo, i18n — or "all" (default).

For broad questions like "what can be improved" or "find all issues", use categories: ["all"]. For mobile apps (React Native/Expo), use ["mobile", "react", "typescript", "accessibility", "performance", "security"]. For web apps, use ["react", "nextjs", "typescript", "security", "accessibility", "performance", "layout", "css", "seo"].

If doc fetches fail with empty results, the user likely needs to set GT_GITHUB_TOKEN for higher GitHub API rate limits. The audit patterns themselves always run locally — only the fix guidance fetch requires network.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokensNoMax tokens per best-practice fetch
maxFilesNoMax source files to scan
categoriesNoIssue categories to audit. Use "all" for broad questions. Default: all. Available: layout, performance, accessibility, security, react, nextjs, typescript, node, python, vue, svelte, angular, testing, mobile, api, css, seo, i18n.
projectPathNoProject directory. Defaults to current working directory.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv5.2.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds that audit patterns run locally and only fix guidance fetch requires network, along with token requirement. This adds useful 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with core function and sibling distinction. It is well-organized but somewhat verbose, containing repeated enumeration of categories. Could be more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (18 categories, multiple use cases), the description covers return format (file:line), error handling (token issue), and usage guidance. No output schema, but the return description is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description enriches the categories parameter with example combinations for mobile and web apps. For tokens and maxFiles, description doesn't add much beyond schema, but overall it compensates adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it scans source files for code issues across 18 categories and fetches best-practice fixes. It distinguishes from sibling gt_auto_scan by specifying that this tool audits the user's own source code, while the sibling audits dependencies.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on when to use specific category combinations (e.g., for mobile apps, web apps, broad questions). Also mentions troubleshooting for failed doc fetches (GT_GITHUB_TOKEN). However, it does not explicitly state when not to use the tool.

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

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