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computer_info

Query a computer in BloodHound for its properties, admin rights, group memberships, sessions, and other security relationships.

Instructions

Query computer data from BloodHound. info_type options: info - general computer properties and attributes admin_rights - objects this computer has admin rights on admin_users - users/groups that have admin rights on this computer constrained_delegation - services this computer can delegate to via kerberos constrained_users - users with contained delegation TO this computer controllables - objects this computer can control controllers - principals that have control over this computer dcom_rights - machines this computer can execute DCOM on dcom_users - users/groups with DCOM rights ON this computer group_membership - groups this computer belongs to ps_remote_rights - machines this computer can PSRemote to ps_remote_users - users/groups with PSRemote rights ON this computer rdp_rights - machines this computer can RDP to rdp_users - users/groups with RDP rights ON this computer sessions - users with active sessions on this computer sql_admins - SQL servers this computer is admin on

args:
    computer_id: BloodHound object ID of the computer (required)
    info_type: what to retrieve (default: info)
    limit: Max Results (default 100, useful in large environments)
    skip: Pagination offset (default 0)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNo
limitNo
info_typeNoinfo
computer_idYes
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains defaults and parameter effects but does not disclose output format, pagination behavior beyond skip/limit, or potential side effects (though it is a query tool). This is adequate but not rich.

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 structured with clear bullet points for info_type and args. Every line provides necessary information without redundancy, making it dense and effective.

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?

The description covers the tool's purpose, all parameters, all info_type behaviors, defaults, and required fields. Given no output schema, it is as complete as expected for a query tool, leaving little ambiguity for an agent.

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 the description fully compensates by explaining every parameter, listing all info_type options with their meanings, and providing defaults for limit, skip, and info_type. This adds significant meaning beyond the bare 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 'Query computer data from BloodHound' with a specific verb and resource, and enumerates distinct info_type options. This distinguishes it from sibling tools like user_info and group_info by focusing on computer-specific data.

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 detailed context for each info_type, making it clear what to use for various retrieval needs. However, it does not explicitly mention alternative tools or scenarios where this tool should not be used, which would strengthen the guidance.

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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