Skip to main content
Glama

modelscan_scan

Scan machine learning models for unsafe serialization, malicious patterns, and security risks in local files or downloadable URLs.

Instructions

Run modelscan against a local path or downloadable URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo
urlNo
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does at a high level ('Run modelscan'), without revealing any behavioral traits such as what 'modelscan' actually scans for (e.g., security vulnerabilities, malicious code), whether it's read-only or destructive, what permissions are needed, expected runtime, output format, or error conditions. This leaves the agent with insufficient information to understand the tool's behavior.

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?

The description is a single, efficient sentence that directly states the tool's function without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly. Every word earns its place by conveying essential information about the action and target.

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

Completeness2/5

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

Given the complexity of a security scanning tool with no annotations, 2 parameters with 0% schema coverage, and no output schema, the description is incomplete. It fails to explain what 'modelscan' entails (e.g., scanning for what types of issues), what the output looks like, error handling, or usage constraints. This leaves significant gaps for an agent to understand and invoke the tool effectively.

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

Parameters2/5

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

The input schema has 0% description coverage, so the description must compensate. It mentions 'a local path or downloadable URL', which hints at the purpose of the 'path' and 'url' parameters but doesn't explain their semantics, constraints, or relationship (e.g., whether both can be provided, if one is required, what formats are accepted, or what happens if neither is given). This adds minimal value beyond the parameter names.

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

Purpose4/5

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

The description clearly states the action ('Run modelscan') and the target ('against a local path or downloadable URL'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'picklescan_scan' or 'deep_model_inspect', which likely perform similar security scanning functions on different targets or with different methodologies.

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. With sibling tools like 'artifact_safety_report', 'deep_model_inspect', 'picklescan_scan', and 'scan_directory_tool' available, there's no indication of what makes 'modelscan_scan' the appropriate choice for a given scenario. No exclusions, prerequisites, or contextual recommendations are mentioned.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/itsalissonsilva/ModelSafetyMCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server