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consensus_analysis

Get multi-auditor consensus for any package. See scan counts, agreement on findings, and overall risk level for a second opinion on security.

Instructions

Get multi-auditor consensus analysis for a package. Shows how many different auditors and models have scanned the package, their agreement on findings, and the overall consensus risk level. Useful for getting a second opinion on any package's security posture.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
package_nameYesPackage name or slug to look up consensus for (e.g., "fastmcp", "mongodb-mcp-server")
Behavior3/5

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

No annotations are provided, so the description must convey behavioral traits. The verbs 'Get' and 'Shows' imply a read-only operation, but the description does not explicitly state that it avoids side effects, permissions, or rate limits. It partially discloses behavior by describing the output, but lacks a clear safety guarantee.

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 two concise sentences. The first sentence immediately states the core function, and the second adds useful details about what is shown and a usage hint. There is no redundant or filler content.

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?

For a simple tool with one parameter and no output schema, the description adequately explains the return content: number of auditors/models, agreement, and consensus risk level. It lacks details about edge cases or how to interpret risk levels, but overall it is sufficiently complete for an agent to invoke correctly.

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?

The schema covers 100% of parameter descriptions, including an example ('fastmcp', 'mongodb-mcp-server'). The tool description adds minimal extra meaning beyond mentioning 'package' and the context of security posture. Since the schema already does the heavy lifting, the baseline score of 3 is appropriate.

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 starts with a specific verb+resource: 'Get multi-auditor consensus analysis for a package.' It clearly explains what the tool does and distinguishes itself from single-audit tools by emphasizing 'multi-auditor' and 'consensus.' The additional detail about showing counts, agreement, and risk level makes the purpose unambiguous.

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: 'Useful for getting a second opinion on any package's security posture.' This signals when to use the tool, particularly as a cross-check on findings. However, it does not explicitly mention alternatives or state when not to use this tool, so it misses the highest bar for sibling differentiation.

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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