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cypher_query

Run and manage Cypher queries in BloodHound, including interpreting natural language, validating, saving, sharing, and exporting queries for attack path analysis.

Instructions

Execute and manage Cypher queries in BloodHound.

info_type options:
    run - execute a cypher query (needs: query; optional: include_properties)
    interpret - interpret a natural language query into cypher (needs: query, result_json)
    list_saved - list saved queries (optional: name, skip, limit)
    create_saved - save a new query (needs: name, query)
    get_saved - get details of a saved query (needs: query_id)
    update_saved - update an existing saved query (needs: query_id; optional: name, query, description)
    delete_saved - delete a saved query (needs: query_id)
    share_saved - share a saved query with other users (needs: query_id; optional: user_ids, public)
    saved_permissions - get saved query permissions (needs: query_id)
    export_saved - export a saved query (needs: query_id)
    import_saved - import saved queries (needs: payload_json)
    export_saved_many - export saved queries (optional: query_ids)
    validate - validate a cypher query for syntax and semantics (needs: query)

args:
    info_type: Operation to perform
    query: Cypher query string (for run, create_saved, update_saved, validate)
    include_properties: Include node/edge properties in results (for run, default: True)
    name: Query name (for create_saved, update_saved, list_saved filter)
    query_id: Saved query ID (for get_saved, update_saved, delete_saved, share_saved)
    result_json: JSON result string from a previous run (for interpret)
    description: Query description (for update_saved)
    user_ids: Comma-separated user IDs to share with (for share_saved)
    query_ids: Comma-separated saved query IDs to export
    payload_json: JSON string/object for saved query import
    public: Make query public (for share_saved, default: False)
    limit: Max results (default 100)
    skip: Pagination offset (default 0)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
skipNo
limitNo
queryNo
publicNo
query_idNo
user_idsNo
info_typeYes
query_idsNo
descriptionNo
result_jsonNo
payload_jsonNo
include_propertiesNo
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It names operations like 'delete_saved' and 'update_saved' but does not mention side effects, permanence, permission requirements, or return behavior. The destructive nature of delete is only implicit through the operation name, leaving significant transparency gaps.

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?

Despite being long, the description is logically structured into 'info_type options' and 'args', with each item earning its place. It is front-loaded with a clear purpose statement and uses a consistent needs/optional format. No fluff or redundancy.

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 the tool's complexity (13 params, 13 operation modes, no output schema), the description covers operations and parameters well. However, it omits return value formats, error handling, and any examples, leaving the agent to guess what outputs to expect from actions like 'run' or 'interpret'.

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%, so the description must fully compensate. It does so by listing all 13 parameters and explaining each one's purpose and applicable operations. This adds substantial meaning beyond the bare schema fields.

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 executes and manages Cypher queries in BloodHound. The verb 'Execute and manage' plus the resource 'Cypher queries' distinguishes it from sibling info tools like domain_info or graph_analysis. The enumerated info_type operations further clarify its scope.

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 per-operation guidance (needs vs optional parameters), giving clear context for each action. However, it does not explicitly state when to choose this tool over siblings or provide exclusion criteria, so it falls short of a perfect 5.

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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