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goklab

guardvibe

analyze_cross_file_dataflow

Detect cross-file injection vulnerabilities by tracing tainted user input across module boundaries. Resolves imports, builds module graphs, and tracks data flow from HTTP handlers to dangerous sinks.

Instructions

Track user input flowing across module boundaries — detects injection vulnerabilities that span multiple files. Resolves imports/exports, builds a module graph, and follows tainted data from HTTP handlers through helper functions to dangerous sinks (SQL, eval, redirect, file ops). Pass all related files for best results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesYesList of files to analyze: [{path, content}]
formatNoOutput formatmarkdown
Behavior4/5

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

With no annotations provided, the description carries the full burden and successfully discloses the analysis methodology: resolving imports/exports, building module graphs, and tracking tainted data to specific dangerous sinks (SQL, eval, redirect, file ops). Missing safety disclosures (read-only status, performance characteristics) prevent a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

Three sentences, zero waste. First sentence establishes purpose and scope, second details technical implementation (methodology), third provides operational guidance. Well-structured with high information density and no redundant phrasing.

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?

For a complex static analysis tool with no output schema, the description adequately explains the analysis mechanism and vulnerability targets. Could be improved by describing the expected return structure (markdown/JSON contents) since no output schema exists to document this.

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?

While schema coverage is 100% (baseline 3), the description adds crucial semantic context for the 'files' parameter: 'Pass all related files for best results' clarifies that the array should include interconnected modules rather than arbitrary isolated files. No additional context provided for 'format' parameter.

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 opens with a specific verb-resource pair ('Track user input flowing across module boundaries') and explicitly defines the scope ('detects injection vulnerabilities that span multiple files'). It clearly distinguishes from sibling tool 'analyze_dataflow' by emphasizing cross-module resolution and multi-file taint tracking.

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 clear contextual guidance through 'Pass all related files for best results,' implying when to use this tool (multi-file scenarios). However, it stops short of explicitly naming alternatives like 'analyze_dataflow' or stating when NOT to use this tool (e.g., single-file analysis).

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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