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honeylabs-mcp

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ioc_lookup_tool

Look up IP or domain reputation in honeypot dataset. Returns total events, first/last seen, country, ASN, targeted ports, user agents, URL paths, and fingerprints.

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

Behavior3/5

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

No annotations are provided, so the description must carry the full burden. It details the return fields (e.g., total_events, first_seen, country, ASN) and states it covers IPv4 and domains, but does not disclose whether the tool is read-only, any authentication or rate limiting, or other behavioral traits beyond the output description.

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 compact and well-structured: it starts with the action, followed by clear usage triggers, then lists the return fields. Every sentence adds value, with no redundancy or filler.

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?

Given the tool's simplicity (one parameter, no annotations) and the existence of an output schema (presumably detailing return fields), the description is largely complete for an agent to select and invoke it correctly. Minor gaps include the precise parameter format and explicit safety indications, but these are not critical for basic usage.

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

Parameters2/5

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

The schema has one required parameter 'ioc' with no description (0% coverage). The high-level description states it accepts IP addresses or domains, but does not specify formats, validation, or examples beyond the trigger phrases. This provides minimal added meaning over the schema's 'string' type.

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: looking up IP addresses or domains in a honeypot dataset. It provides specific user queries that trigger this tool, distinguishing it from siblings like asn_enrich_tool and attack_timeline_tool which serve different functions.

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 explicitly says 'Use this FIRST whenever the user asks...' and lists example queries, providing clear context for when to invoke the tool. However, it does not mention exclusions or when not to use it, nor does it reference alternatives beyond the implicit suggestion that this is the primary lookup tool.

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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