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hmc_create_password_policy

Create a new HMC password policy specifying age limits, minimum length, character class counts, and history size to enforce password rules.

Instructions

Create a new HMC password policy.

policy_name is the unique name for the policy. pwage is the maximum password age in days (0 = never expires). min_length is the minimum password length. min_digits, min_uppercase, min_lowercase, and min_special set character-class minimums. hist_size controls how many previous passwords cannot be reused. warn_pwage is the number of days before expiry to warn the user. min_pwage is the minimum days before a password may be changed. Confirm the policy_name before calling. Returns the created policy resource dict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pwageNo
hist_sizeNo
min_pwageNo
min_digitsNo
min_lengthNo
warn_pwageNo
min_specialNo
policy_nameYes
min_lowercaseNo
min_uppercaseNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description explains each parameter's effect in detail and states the return value ('Returns the created policy resource dict'). However, it does not disclose what happens on duplicate policy_name, whether the operation requires specific permissions, or any side effects. With no annotations, this is a notable 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 well-structured: a single opening sentence states the purpose, followed by a compact list of parameter definitions, a usage tip, and a closing return statement. No wasted words; everything is relevant.

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?

For a create operation with 10 parameters and no schema descriptions, the description covers all parameter semantics, the return value, and a usage caution. It lacks details on error handling or idempotency, but the presence of an output schema mitigates the need for return explanation.

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 description coverage is 0%, yet the description compensates fully by explicitly defining the meaning of every parameter (pwage, min_length, hist_size, etc.) in plain language. This exceeds the baseline and adds significant value beyond 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 opens with a specific verb+resource: 'Create a new HMC password policy.' This clearly distinguishes the tool from its siblings (modify/delete/list) and immediately states the tool's core action.

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 gives clear context for when to use the tool (creating a new policy) and includes a practical tip: 'Confirm the policy_name before calling.' However, it does not explicitly compare with alternatives like modify or delete, so it lacks the when-not-to-use 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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