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AI Inventory Scan

ai_inventory_scan
Read-onlyIdempotent

Scan source code to identify AI SDK imports, model references, API keys, and shadow AI across multiple programming languages. Find where AI components are used in your codebase.

Instructions

Scan source code for AI component usage patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
directoryYesDirectory to scan for AI SDK imports, model refs, API keys, shadow AI (Python/JS/TS/Java/Go/Rust/Ruby).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already convey readOnlyHint, destructiveHint, and idempotentHint. The description adds minimal behavioral context beyond 'scan source code', which aligns with annotations. No contradictions, but no additional traits disclosed.

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?

Single sentence that is front-loaded with the core action. Every word is necessary and 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 presence of annotations, output schema, and a single well-documented parameter, the description is sufficiently complete for the tool's simplicity. Slightly more context on output could push to 5.

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 parameter description is rich, specifying file types and scanned elements (SDK imports, model refs, API keys, shadow AI). This adds meaning beyond the schema type.

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 the verb 'scan', the resource 'source code', and the specific object 'AI component usage patterns'. It effectively distinguishes from sibling tools like 'code_scan' or 'scan' by specifying AI focus.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives or any prerequisites. It simply states the action without contextual usage advice.

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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