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honeylabshq

honeylabs-mcp

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ioc_lookup_tool

Query an IP address or domain against 90 days of honeypot data to assess malicious activity and known scanner behavior.

Instructions

Look up any IP address or domain in the honeypot dataset. Use this FIRST whenever the user asks: 'is this IP malicious?', 'is this a known scanner?', 'have you seen this IP?', 'what does this IP do?', 'when was it last seen?', 'is this IP in your data?'. Returns: total_events (0 = never observed), first_seen, last_seen, country, ASN, all ports targeted, top user agents, top URL paths, TLS/HTTP/SSH fingerprints. Covers both IPv4 and domains.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
iocYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description carries full burden. It details return fields with meanings (e.g., 'total_events (0 = never observed)'), covers both IPv4 and domains, and implies read-only behavior for a lookup tool.

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?

Three well-structured sentences: action, example queries, return list. No redundant information, and purpose is front-loaded.

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

Completeness5/5

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

Output schema exists, but description still covers return values. With one parameter fully explained and low complexity, the description provides complete context for selecting and invoking the tool.

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

Parameters5/5

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

Schema coverage is 0%, but description fully explains the single parameter 'ioc' as 'any IP address or domain', adding clear meaning beyond the type definition.

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 it looks up IPs or domains in a honeypot dataset, with specific verbs ('look up') and resources. It includes example queries and differentiates by suggesting 'Use this FIRST', distinguishing it from sibling tools like fingerprint_search_tool or payload_search_tool.

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?

Provides explicit usage context with example user questions and instruction 'Use this FIRST'. Lacks explicit when-not-to-use or alternatives, but the context strongly implies appropriate scenarios.

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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