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konstruktoid

prescryb

by konstruktoid

generate_playbook

Generate a suggest-only Ansible playbook that remediates CVE matches and compliance gaps without executing it. Review with ansible-playbook --check before applying.

Instructions

Generate a suggest-only Ansible playbook from findings. Does NOT run it.

`system`: object from inventory_host. `cve_matches`: entries from
check_cves you want remediated (each becomes a package-upgrade task
citing the CVE). `compliance_areas`: topic hints (e.g. ["ssh", "sudo"])
- each resolved via map_compliance and, where a matching
konstruktoid.hardening role exists, referenced in the playbook's
`roles:` list instead of reimplemented. The header also cites the MITRE
ATT&CK techniques/mitigations each area addresses. Always review the
output with `ansible-playbook --check --diff` before applying.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
systemYes
cve_matchesNo
hosts_aliasNo
compliance_areasNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description fully discloses key behavioral traits: the playbook is 'suggest-only' and not executed, output should be reviewed with 'ansible-playbook --check --diff', compliance areas are resolved via map_compliance and may reference a hardening role, and MITRE ATT&CK techniques are cited. This goes beyond what any annotations would provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise given the complexity, front-loaded with the main purpose, and uses clear structure with code formatting. A few redundant phrases could be trimmed, but overall it earns its keep.

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 tool with 4 parameters, nested objects, and existing output schema, the description is thorough. It explains the input sources, parameter behavior, and post-generation step, though it doesn't detail the return format beyond suggesting it's a YAML playbook.

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?

Despite 0% schema coverage, the description adds significant meaning: 'system' is an object from inventory_host, 'cve_matches' become package-upgrade tasks, and 'compliance_areas' are topic hints resolved via map_compliance. However, 'hosts_alias' is not explained, leaving a gap.

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 'Generate a suggest-only Ansible playbook from findings. Does NOT run it.' This specific verb-resource pair and the explicit exclusion of execution make the purpose unmistakable and distinct from siblings that perform checks or lookups.

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 context on when to use the tool: after inventory_host, check_cves, and map_compliance. It explains the role of each parameter, but does not explicitly state when not to use it or compare directly to alternative tools.

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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