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honeylabshq

honeylabs-mcp

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attack_timeline_tool

Track attack volume over time with hourly or daily buckets. Filter by protocol, country, or port to identify trends and spikes.

Instructions

Attack volume over time, bucketed by hour or day. Use for: 'show attack trends this week', 'was there a spike on port 22?', 'how has SSH scanning changed?', 'attack volume from China over 30 days'. bucket: 'hour' or 'day'. Optional filters: filter_protocol ('tls'/'''), filter_country (2-letter code), filter_dest_port. since/until ISO-8601 UTC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceYes
untilYes
bucketNoday
filter_protocolNo
filter_countryNo
filter_dest_portNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It only states that data is bucketed and filterable, but fails to disclose whether the tool is read-only, whether mutations occur, or any side effects or limitations. This lack of safety information is a significant gap.

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 and front-loaded with the core purpose. Every sentence adds value, and the structure is logical with examples first followed by parameter clarifications. No wasted words.

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 has 6 parameters, no annotations, and an output schema exists, the description covers the main functional aspects well. However, it lacks behavioral details (read-only? rate limits?) and does not hint at response structure or data volume limits, which could be relevant for an agent invoking it.

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?

The schema description coverage is 0%, yet the description adds substantial meaning: it explains bucket valid values ('hour' or 'day'), format for filter_country (2-letter code), filter_protocol allowed values ('tls' or null), and date format for since/until (ISO-8601 UTC). This fully compensates for the absence of parameter documentation in the schema.

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 'Attack volume over time, bucketed by hour or day' and provides specific example queries, making the purpose very clear. It effectively distinguishes itself from sibling tools by focusing on temporal volume trends rather than individual event details.

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 explicit example use cases like 'show attack trends this week' and 'was there a spike on port 22?', which gives clear context for when to use the tool. However, it does not mention when not to use it or list alternative tools, which would further aid selection.

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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