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risk_posture

Assess security posture by querying current statistics or historical risk data from BloodHound Enterprise.

Instructions

Query BloodHound Enterprise risk posture data.

info_type options:
    stats - get current posture statistics
    history - get posture history for a data type (needs: data_type)

args:
    info_type: what to retrieve (default: stats)
    data_type: posture history data type for history queries

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
data_typeNo
info_typeNostats
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the two behavioral modes (stats and history) and the prerequisite for history, but does not mention read-only nature explicitly, error handling, or response format. The behavioral info is present but minimal.

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 succinct, with a clear opening sentence followed by an organized list of options. Every sentence adds informative value, and it's front-loaded with the purpose. No unnecessary words.

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

Completeness3/5

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

Given no output schema and no annotations, the description should cover return values, but it doesn't specify what the statistics or history response contains. It adequately explains parameters and query types, but for a standalone tool, key details about output shape are missing. It's sufficient for basic usage but not fully complete.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must add meaning. It does explain info_type values ('stats' and 'history') and that data_type is needed for history queries, which goes beyond the plain schema. However, data_type remains vague, without listing valid data types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Query BloodHound Enterprise risk posture data' with a specific verb and resource. It further breaks down info_type options (stats and history), making the tool's purpose unmistakable. While it doesn't explicitly contrast with sibling tools, the resource name is distinct enough.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides usage context by explaining the info_type options and that history requires data_type. However, it does not mention when to use this tool over related siblings like data_quality or enterprise_info, nor any exclusions. This is implied usage rather than explicit 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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