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hound_typosquat

Detect typosquatting in package names by generating typo variants and checking registry availability to prevent supply chain attacks.

Instructions

Check if a package name looks like a typosquat of a popular package. Generates likely typo variants and checks which ones exist in the registry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesPackage name to check
ecosystemNoPackage ecosystem (default: npm)npm
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool generates likely typo variants and checks registry existence, but doesn't describe what 'likely' means, how many variants are generated, whether this is a read-only operation, what permissions are needed, rate limits, or what the output format looks like. Significant behavioral details are missing.

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 extremely concise (two sentences) and front-loaded with the core purpose. Every word earns its place, with no redundant or verbose language. It efficiently communicates the tool's functionality without unnecessary elaboration.

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 tool's complexity (generating variants and checking registries), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what constitutes a 'popular package', how variant generation works, what registry is checked, or what the output contains. For a security-focused analysis tool, this leaves too many gaps.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already fully documents both parameters (name and ecosystem). The description doesn't add any parameter-specific details beyond what's in the schema, such as explaining how the name parameter is processed or clarifying ecosystem implications. Baseline 3 is appropriate when the schema does all the work.

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 tool's purpose with specific verbs ('Check', 'Generates', 'checks') and resources ('package name', 'typo variants', 'registry'), distinguishing it from sibling tools focused on advisories, audits, licenses, etc. It explains both the analysis (generating typo variants) and verification (checking registry existence) aspects.

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 like hound_audit or hound_vulns, nor does it mention prerequisites, constraints, or typical use cases. It simply states what the tool does without contextual usage information.

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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