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create_dfw_policy

Create a new Distributed Firewall security policy, defining its category, priority, and stateful tracking. This creates an empty policy container ready for DFW rules to be added separately.

Instructions

[WRITE] Create a new DFW security policy.

Returns the created policy dict (id, path, category, ...), else {"error", "hint"}. The policy is an empty container — rules must be added afterwards with create_dfw_rule.

Args: policy_id: Unique policy id (alphanumerics, hyphens, underscores). display_name: Human-readable name. category: Ethernet, Emergency, Infrastructure, Environment or Application (default Application); sets DFW evaluation order, Ethernet first, Application last. sequence_number: Priority; lower = higher priority (default 10). stateful: Track connection state (default True). description: Optional description. target: Optional NSX Manager target from config.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNo
categoryNoApplication
statefulNo
policy_idYes
descriptionNo
display_nameYes
sequence_numberNo
Behavior4/5

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

Annotations already indicate a write operation (readOnlyHint=false). The description adds useful context: it returns the created policy dict or an error/hint, and emphasizes that the policy starts as an empty container. This goes beyond annotation basics, yet it omits details like permission requirements or side effects, keeping it at a 4.

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 well-structured: purpose, return value, usage note, then a parameter list. Every sentence is informative and none are redundant. It is concise yet comprehensive, fitting the tool's complexity.

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?

With no output schema, the description covers return values and error format. It also explains the 'empty container' behavior and dependency on create_dfw_rule. Some minor aspects like error scenarios or required permissions are brief, but overall it is sufficiently complete for a 7-parameter tool.

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 has 0% description coverage, but the description provides rich semantics for all 7 parameters: policy_id uniqueness constraints, category allowed values, sequence_number priority meaning, stateful default, and target usage. It fully compensates for the sparse 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 'Create a new DFW security policy' with a specific verb and resource. This distinguishes it from sibling tools like create_dfw_rule, get_dfw_policy, and update_dfw_policy, making the tool's purpose unambiguous.

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 clear workflow context: 'The policy is an empty container — rules must be added afterwards with create_dfw_rule.' It also explains category evaluation order, which helps selection. However, it does not explicitly mention when not to use this tool or alternative scenarios, so it slightly misses the top score.

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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