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vsl8
by vsl8

ansible-auto-heal

Automatically resolve issues on target hosts by providing symptoms, with safety checks and configurable impact limits.

Instructions

Intelligent automated problem resolution with safety checks.

Args: host_pattern: Target hosts pattern symptoms: List of detected symptoms project_root: Project root directory ansible_cfg_path: Ansible config file path inventory_paths: Inventory file paths max_impact: Maximum allowed impact level (low, medium, high) dry_run: Preview actions without executing

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNo
symptomsYes
max_impactNolow
host_patternYes
project_rootNo
inventory_pathsNo
ansible_cfg_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

Without annotations, the description must fully disclose behavioral traits. It mentions 'safety checks' and a 'dry_run' parameter for preview, which hints at cautious mutation. However, it does not explain what actions are taken, whether state changes occur, permissions needed, or potential side effects. For a tool that likely modifies systems, this is insufficient.

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 short and includes a clear 'Args:' list. It front-loads the core purpose in the first line. However, the parameter descriptions are terse and could be more detailed without bloating.

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?

The description covers the basic purpose and parameters but lacks information on return values or execution outcomes. Given that an output schema exists (as per context signals), the omission is partially mitigated. Still, for a tool that performs healing actions, more detail on success/error behavior would improve completeness.

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 coverage is 0%, so the description must add meaning. It lists all 7 parameters with brief explanations beyond the schema titles (e.g., 'max_impact: Maximum allowed impact level (low, medium, high)' adds enum values not present in the schema). This compensates well for the missing schema descriptions.

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 'Intelligent automated problem resolution with safety checks', which identifies the tool's function as automated healing. This distinguishes it from sibling tools like 'ansible-diagnose-host' or 'ansible-health-monitor' that focus on detection rather than resolution.

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

Usage Guidelines2/5

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

No explicit guidance is given on when to use this tool versus alternatives. The description implies it should be used after symptoms are detected, but does not mention prerequisites, conditions for use, or situations where other tools (e.g., manual playbooks) would be more appropriate.

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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