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hound_popular

Scan popular packages for known vulnerabilities to identify security issues in widely-used dependencies across multiple ecosystems.

Instructions

Scan a list of popular (or user-specified) packages for known vulnerabilities. Quickly surface which widely-used packages in an ecosystem have open security issues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ecosystemNoPackage ecosystem (default: npm)npm
packagesNoSpecific package names to check. If omitted, uses a curated list of popular packages for the ecosystem.
Behavior3/5

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 describes the tool's behavior (scanning for vulnerabilities, using a curated list if packages are omitted) but lacks details on permissions, rate limits, data sources, or response format. It adequately covers the core operation but misses deeper behavioral traits.

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 appropriately sized and front-loaded, with two concise sentences that directly convey the tool's purpose and usage. Every sentence earns its place by adding essential information without redundancy or unnecessary details.

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

Completeness3/5

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is complete enough for basic understanding but lacks depth. It covers what the tool does and when to use it, but without annotations or output schema, it misses details on behavioral constraints and return values, leaving gaps for an AI agent.

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 documents both parameters fully. The description adds marginal value by explaining the default behavior (using a curated list if packages omitted) and the context of 'popular packages', but does not provide additional syntax or format details beyond what the schema specifies.

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 ('scan', 'surface') and resources ('packages', 'known vulnerabilities', 'open security issues'). It distinguishes from siblings by focusing on popular packages rather than specific audits, advisories, or other security checks, making the scope explicit.

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?

The description provides clear context for usage: scanning popular packages for vulnerabilities, with an option for user-specified packages. It implies when to use this tool (quick checks of widely-used packages) but does not explicitly state when not to use it or name alternatives among the many sibling tools, such as hound_advisories or hound_vulns, for more targeted analyses.

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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