Scans a project directory to detect npm and pip manifests and checks their dependencies against real registries, helping flag slopsquatting risks.
Auto-detect and check both npm and pip manifests (package.json, requirements.txt, pyproject.toml) in a directory against their real registries
| Name | Required | Description | Default |
|---|---|---|---|
| directory | Yes | Path to the project root directory |
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does disclose a key trait beyond the name: the check is performed against real registries, implying network access and external lookups. It omits recursion behavior, failure handling when a registry is unreachable, and any rate-limit or credential expectations.
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?
A single front-loaded sentence with the action first and the target files listed inline; no filler sentences. It is efficient, though the dense parenthetical slightly buries the scope.
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 and no annotations, so the description is the only source of return and safety information. It explains what is scanned but says nothing about the shape of results, severity reporting, or whether the scan is read-only, leaving a real gap for a scanner tool.
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 coverage is 100% and only one parameter exists, so the schema already documents 'directory' fully. The description adds only that the directory is inspected for manifests, which is marginal semantics beyond the schema's 'Path to the project root directory'. Baseline 3 is appropriate.
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 gives a specific verb (auto-detect and check), a clear resource (npm/pip manifests), and even enumerates the concrete files it targets (package.json, requirements.txt, pyproject.toml). It implicitly differentiates itself from scan_npm and scan_pip by covering both ecosystems in one pass, though it never names those siblings explicitly.
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?
Usage is implied by the auto-detection framing: an agent can infer this is the right tool when a directory may contain mixed manifests. However, there is no explicit guidance on when to prefer this over scan_npm, scan_pip, or check_package, and no stated exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.